
  ___  ____  ____  ____  ____ (R)
 /__    /   ____/   /   ____/
___/   /   /___/   /   /___/   13.0   Copyright 1985-2013 StataCorp LP
  Statistics/Data Analysis            StataCorp
                                      4905 Lakeway Drive
     Special Edition                  College Station, Texas 77845 USA
                                      800-STATA-PC        http://www.stata.com
                                      979-696-4600        stata@stata.com
                                      979-696-4601 (fax)

16-user Stata network perpetual license:
       Serial number:  401306212364
         Licensed to:  Econometrics Laboratory
                       UC Berkeley

Notes:
      1.  (-v# option or -set maxvar-) 5000 maximum variables
      2.  Command line editing disabled
      3.  Stata running in batch mode

Note:  Your site can add messages to the introduction by editing the file
       stata.msg in the directory where Stata is installed.

. do structural.do 

. clear all

. set mem 4000m
set memory ignored.
    Memory no longer needs to be set in modern Statas; memory adjustments are
    performed on the fly automatically.

. set matsize 2000

. set maxvar 8000


. 
. use build.dta
(County and City Data Book [United States] Consolidated File: County Data, 1947
> -1)

. 
. 
. ********************************
. * NEW VARIABLES
. ********************************
. 
. * Per capita wage in manufacturing, in real dollars
. * Manufacturing payroll of production workers over average number of producti
> on workers 
. g wage0    = (pcmwage00)/(cpi0/100)
(298 missing values generated)

. g wage20   = (pcmwage20)/(cpi20/100)
(135 missing values generated)

. g wage30   = (pcmwage30)/(cpi30/100)
(426 missing values generated)

. g wage40   = (pcmwage39)/(cpi40/100)
(612 missing values generated)

. g wage50   = (pcmwage47)/(cpi50/100)
(487 missing values generated)

. g wage60   = (pcmwage58)/(cpi60/100)
(416 missing values generated)

. g wage70   = (pcmwage67)/(cpi70/100)
(696 missing values generated)

. g wage80   = (pcmwage82)/(cpi80/100)
(581 missing values generated)

. g wage90   = (pcmwage87)/(cpi90/100)
(664 missing values generated)

. g wage2000 = (pcmwage97)/(cpi2000/100)
(966 missing values generated)

. 
. 
. *use lagwage measures to avoid mechanical correlation between L and w
. replace wage2000=lagwage00 //92 CBP
(2536 real changes made, 1 to missing)

. replace wage90=lagwage90 //82 EC
(2293 real changes made, 111 to missing)

. replace wage80=lagwage80 //72 EC
(2296 real changes made, 180 to missing)

. replace wage70=lagwage70 //62 EC
(2391 real changes made, 64 to missing)

. replace wage60=lagwage60 //52 EC
(2536 real changes made, 83 to missing)

. replace wage50=sqrt(lagwage60*lagwage30) //interpolate
(2452 real changes made, 237 to missing)

. replace wage40=lagwage30  //this comes from 1930 Decennial
(2456 real changes made, 119 to missing)

. 
. 
. 
. * Per capita wage in trade, in real dollars
. * total payroll in wholesale establishments + retail establishments / (total 
> workers in retail+ in wholsale)
. g twage30  = pctwage30/(cpi30/100) 
(147 missing values generated)

. g twage40  = pctwage40/(cpi40/100)
(147 missing values generated)

. g twage50  = pctwage54/(cpi50/100)
(580 missing values generated)

. g twage60  = pctwage63/(cpi60/100)
(123 missing values generated)

. g twage70  = pctwage72/(cpi70/100)
(99 missing values generated)

. g twage80  = pctwage82/(cpi80/100)
(175 missing values generated)

. g twage90  = pctwage87/(cpi90/100)
(272 missing values generated)

. g twage2000  = pctwage97/(cpi2000/100)
(617 missing values generated)

. 
. * Agricultural values
. 
. g lnfaval890 = ln(faval890/(cpi890/100))
(480 missing values generated)

. g lnfaval0 = ln(faval900/(cpi0/100))
(292 missing values generated)

. g lnfaval10 = ln(faval910/(cpi10/100))
(129 missing values generated)

. g lnfaval20 = ln(faval920/(cpi20/100))
(30 missing values generated)

. g lnfaval30 = ln(faval930/(cpi30/100))
(4 missing values generated)

. g lnfaval40 = ln(faval940/(cpi40/100))
(4 missing values generated)

. g lnfaval60 = ln(faval959/(cpi60/100))
(5 missing values generated)

. g lnfaval2000=ln(faval2002/(cpi2000/100))
(6 missing values generated)

. 
. 
. * Median family income
. gen lnmedfaminc50  = ln(medfaminc50/(cpi50/100)) 
(17 missing values generated)

. gen lnmedfaminc60  = ln(medfaminc60/(cpi60/100)) 

. gen lnmedfaminc2000= ln(medfaminc2000/(cpi2000/100))
(2 missing values generated)

. 
. * Farm production
. gen lnvfprod30   = log(vfprod30/(cpi30/100))
(1 missing value generated)

. gen lnvfprod40   = log(vfprod40/(cpi40/100))

. gen lnvfprod60   = log(vfprod60/(cpi60/100))

. gen lnvfprod2000 = log(vfprod2000/(cpi2000/100))
(7 missing values generated)

. 
. *Foreign born
. gen fb0=fbwmtot00 + fbwftot00 
(251 missing values generated)

. gen fb10=fbwtot10
(129 missing values generated)

. gen fb20=fbwmtot20 + fbwftot20 
(26 missing values generated)

. gen fb30=fbwmtot + fbwftot

. 
. gen fbshr20=fb20/(wmtot20 + wftot20)
(26 missing values generated)

. gen fbshr30=fb30/(wmtot + wftot)

. 
. *Housing Values/Rents
. 
. ren medrnt30_NHGIS medrnt30

. ren medhsval30_NHGIS medhsval30

. ren var88_county72 medhsval70

. ren var89_county72 medrnt70

. 
. foreach var in medhsval medrnt{
  2.         foreach yr in 30 40 50 60 70 80 90 2000{
  3.                 cap replace `var'`yr'=`var'`yr'/(cpi`yr'/100)
  4.         }
  5. }

. 
. *various
. drop other60

. 
. *drop counties experiencing big changes in area
. gen d=(b1_lnd01_county00 - area)/(b1_lnd01_county00 + area)/2

. drop if abs(d)>.03
(91 observations deleted)

. replace area=(b1_lnd01_county00 + area)/2
area was long now double
(2578 real changes made)

. 
. 
. 
. ******************************
. * standardize variable names *
. ******************************
. 
. 
. ren emp00 emp0

. ren manuf_jobs_00 manuf_jobs_0

. 
. foreach yr in 0 10 20 30 40 50 60 70 80 90 2000{
  2.         cap drop manuf`yr'
  3.         cap drop agr`yr'
  4.         ren manuf_jobs_`yr' manuf`yr'
  5.         cap ren ag_jobs`yr' agr`yr'
  6. }

. 
. 
. 
. 
. foreach yr in 0 10 20 30 60 2000{
  2.         gen other`yr'=emp`yr'-agr`yr'-manuf`yr'
  3. }
(236 missing values generated)
(120 missing values generated)
(27 missing values generated)
(5 missing values generated)
(2 missing values generated)

. 
. 
. *********************
. *    Make Share     *
. *********************
. 
. foreach var in manuf agr{
  2.         foreach yr in 0 10 20 30 40 60 70 2000{
  3.                 cap gen `var'shr`yr'=`var'`yr'/emp`yr'
  4.         }
  5. }

. 
. ********************
. * prepare outcomes *
. ********************
. 
. 
. foreach var in pop emp house wage twage agr manuf other medhsval medrnt fb {
  2.         cap gen ln`var'0=ln(`var'0)
  3.         cap gen ln`var'10=ln(`var'10)
  4.         cap gen ln`var'20=ln(`var'20)
  5.         cap gen ln`var'30=ln(`var'30)
  6.         cap gen ln`var'40=ln(`var'40)
  7.         cap gen ln`var'50=ln(`var'50)
  8.         cap gen ln`var'60=ln(`var'60)
  9.         cap gen ln`var'70=ln(`var'70)
 10.         cap gen ln`var'80=ln(`var'80)
 11.         cap gen ln`var'90=ln(`var'90)
 12.         cap gen ln`var'2000=ln(`var'2000)
 13. }

. 
. drop lntwage20  lnmedhsval20 lnmedrnt20 //stata confuses 20 and 2000

. 
. 
. *******************
. *Generate Controls*
. *******************
. g urbshare0=popurb0/pop0
(233 missing values generated)

. g urbshare10=popurb10/pop10
(123 missing values generated)

. g urbshare20=popurb20/pop20
(24 missing values generated)

. g urbshare30=popurb30/pop20
(24 missing values generated)

. gen popdens0=pop0/b1_lnd01_county00
(233 missing values generated)

. 
. 
. *fix zeros in covariate quantities
. 
. foreach var in agr manuf other{
  2.         foreach yr in 10 20 30{
  3.                 cap replace ln`var'`yr'=0 if `var'`yr'<=0
  4.                 gen no`var'`yr'dum=`var'`yr'<=0
  5.         }
  6. }

. 
. ren mfgcap00 mfgcap0

. gen lnmfgcap0=ln(mfgcap0)
(273 missing values generated)

. replace lnmfgcap0=0 if mfgcap0==0
(7 real changes made)

. 
. 
. 
. *fix wages
. 
. foreach var in wage twage{
  2.         foreach yr in 20 30{
  3.                 cap replace ln`var'`yr'=-1 if `var'`yr'==.
  4.                 cap gen no`var'`yr'dum=`var'`yr'==.
  5.         }
  6. }

. 
. 
. 
. *transformations
. foreach var of varlist elevmax elevrang popdens0 tillit10 tillit1020 tillit10
> 10 retsales radiorep totunemp area{
  2.         gen ln`var'=ln(`var')
  3. }
(233 missing values generated)
(24 missing values generated)
(118 missing values generated)
(1 missing value generated)
(6 missing values generated)

. 
. 
. center tmean* lnelevmax

. 
. foreach var of varlist c_lnelevmax white0 white20 white30 c_tmean* lnmanuf0 l
> nmanuf10 lnmanuf20 lnradiorep lnemp20 lnemp30 lnwage0 lnwage20 lnwage30 lntwa
> ge30 lnpop0 lnpop20 lnpop30 lnfaval0 lnfaval20 lnfaval30 tmean*{
  2.         gen `var'sq=`var'^2
  3.         gen `var'cub=`var'^3
  4. }
(233 missing values generated)
(233 missing values generated)
(24 missing values generated)
(24 missing values generated)
(900 missing values generated)
(900 missing values generated)
(120 missing values generated)
(120 missing values generated)
(27 missing values generated)
(27 missing values generated)
(1 missing value generated)
(1 missing value generated)
(27 missing values generated)
(27 missing values generated)
(277 missing values generated)
(277 missing values generated)
(233 missing values generated)
(233 missing values generated)
(24 missing values generated)
(24 missing values generated)
(274 missing values generated)
(274 missing values generated)
(28 missing values generated)
(28 missing values generated)
(4 missing values generated)
(4 missing values generated)

. 
. gen popdifsq=(lnpop30-lnpop20)^2
(24 missing values generated)

. gen empdifsq=(lnemp30-lnemp20)^2
(27 missing values generated)

. gen manufdifsq=(lnmanuf20-lnmanuf0)^2
(900 missing values generated)

. gen urbsharedifsq=(urbshare20-urbshare0)^2
(233 missing values generated)

. gen whitedifsq=(white20-white0)^2
(233 missing values generated)

. gen agrdifsq=(lnagr20-lnagr0)^2
(255 missing values generated)

. gen wagedifsq=(lnwage20-lnwage0)^2
(277 missing values generated)

. gen favaldifsq=(lnfaval20-lnfaval0)^2
(274 missing values generated)

. 
. gen agrshr30sq=agrshr30^2
(5 missing values generated)

. gen agrshr20sq=agrshr20^2
(27 missing values generated)

. 
. gen lnagr20sq=lnagr20^2
(27 missing values generated)

. gen lnagr0sq=lnagr0^2
(255 missing values generated)

. gen fbdifsq=(lnfb20-lnfb0)^2
(251 missing values generated)

. 
. gen wagedif2sq=(lnwage30-lnwage20)^2

. gen tmean_jan_jul=tmean_jan*tmean_jul

. 
. gen pctil20=tillit1020/t10tot20
(24 missing values generated)

. gen pctil30=tillit10/t10tot

. replace PRADIO=PRADIO/100
(2671 real changes made)

. gen urate30=totunemp/(totunemp+emp30)

. 
. 
. global X "lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30 lnpop30sq pop
> difsq agrshr20 agrshr20sq agrshr30 agrshr30sq manufshr20 manufshr30 nowage20 
> nowage30 lnwage20 lnwage30 notwage30 lntwage30 lnemp20 lnemp30 urbshare20 urb
> share30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30 white20 white20sq white30
>  white30sq pctil20 pctil30 PRADIO urate30 fbshr20 fbshr30"

. 
. run "~/geo/x_ols_JP_v10.ado" //use Juan Pablo's version of Conley (1999)

. run "~/geo/bo2_JP.ado" //use Juan Pablo's version of O-B

. global tables="~/latex/tables_raw"

. 
. 
. 
. *******************************************
. *******************************************
. * Propensity score 
. *******************************************
. *******************************************
. 
. sum $X

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
   lnelevmax |      2672     7.18372    1.127627   2.833213   9.581491
  lnelevrang |      2672    6.472382    1.267688    2.70805   9.592332
      lnarea |      2672    6.550518    .7363313   3.198673   9.909171
     lnpop20 |      2648    9.856253    .9216612   6.940222   14.93164
   lnpop20sq |      2648    97.99487    18.78028   48.16668   222.9539
-------------+--------------------------------------------------------
     lnpop30 |      2672    9.897864    .9736989   7.234177   15.19733
   lnpop30sq |      2672    98.91544    20.09119   52.33332   230.9587
    popdifsq |      2648    .0424405     .154054   1.18e-09   5.376893
    agrshr20 |      2645    .5133317    .2393428          0          1
  agrshr20sq |      2645    .3207728    .2386314          0          1
-------------+--------------------------------------------------------
    agrshr30 |      2667    .4751176    .2317202          0          1
  agrshr30sq |      2667    .2794108    .2180256          0          1
  manufshr20 |      2645    .1183587    .1377249          0          1
  manufshr30 |      2672    .0854374    .1086329          0   1.042577
 nowage20dum |      2672    .0475299    .2128093          0          1
-------------+--------------------------------------------------------
 nowage30dum |      2672    .1534431    .3604816          0          1
    lnwage20 |      2672    1.443184    .6125392         -1   2.730856
    lnwage30 |      2672    1.344912    1.049209         -1   2.620676
notwage30dum |      2672    .0508982     .219831          0          1
   lntwage30 |      2672     1.79669    .6722974         -1   2.398963
-------------+--------------------------------------------------------
     lnemp20 |      2645     8.79458    .9977833    4.61512    14.1185
     lnemp30 |      2672    8.884856    1.007512   6.322565   14.40485
  urbshare20 |      2648    .1999792    .2415469          0          1
  urbshare30 |      2648    .2628718     .331775          0   2.933782
   lnfaval20 |      2644    5.641551    .8236685   2.995732   9.012499
-------------+--------------------------------------------------------
   lnfaval30 |      2668    5.574193    .8236583   2.482908   10.30676
lnmedhsval30 |      2619    9.546574    .4832749   8.073895   11.36807
  lnmedrnt30 |      2622    8.990487    .4435811   7.851218   10.34694
     white20 |      2648     .889634    .1831826   .0921502          1
   white20sq |      2648    .8249917    .2627823   .0084917          1
-------------+--------------------------------------------------------
     white30 |      2672    .8763055    .1838349   .1406302          1
   white30sq |      2672    .8016939    .2672737   .0197768          1
     pctil20 |      2648    .0650953    .0747869   .0015806   .5655269
     pctil30 |      2672    .0497284    .0558682   .0004784    .502906
    PRADIO30 |      2672    .2738112    .1759582          0      .7777
-------------+--------------------------------------------------------
     urate30 |      2672     .027643    .0200907          0    .139693
     fbshr20 |      2648    .0770435    .0822638          0   .5354601
     fbshr30 |      2672    .0543065    .0612852          0    .320442

. 
. logit tva $X, cluster(state)

note: nowage20dum != 0 predicts failure perfectly
      nowage20dum dropped and 83 obs not used

Iteration 0:   log pseudolikelihood = -601.86167  
Iteration 1:   log pseudolikelihood = -500.33539  
Iteration 2:   log pseudolikelihood = -332.80519  
Iteration 3:   log pseudolikelihood = -289.12204  
Iteration 4:   log pseudolikelihood = -275.34548  
Iteration 5:   log pseudolikelihood =  -267.2652  
Iteration 6:   log pseudolikelihood = -260.85231  
Iteration 7:   log pseudolikelihood = -259.79296  
Iteration 8:   log pseudolikelihood = -259.78068  
Iteration 9:   log pseudolikelihood = -259.78068  

Logistic regression                               Number of obs   =       2489
                                                  Wald chi2(22)   =          .
                                                  Prob > chi2     =          .
Log pseudolikelihood = -259.78068                 Pseudo R2       =     0.5684

                                 (Std. Err. adjusted for 47 clusters in state)
------------------------------------------------------------------------------
             |               Robust
         tva |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   lnelevmax |   1.990741   .5065591     3.93   0.000     .9979037    2.983579
  lnelevrang |  -.9499507   .4032203    -2.36   0.018    -1.740248   -.1596535
      lnarea |  -1.854763   .5782767    -3.21   0.001    -2.988164    -.721361
     lnpop20 |  -50.50022   18.45222    -2.74   0.006    -86.66591   -14.33454
   lnpop20sq |   2.352819   .9994147     2.35   0.019     .3940016    4.311635
     lnpop30 |    26.5316   17.99592     1.47   0.140    -8.739759    61.80296
   lnpop30sq |  -1.389389    .940212    -1.48   0.139    -3.232171    .4533925
    popdifsq |  -19.60975   4.012243    -4.89   0.000     -27.4736    -11.7459
    agrshr20 |  -6.643038   2.228576    -2.98   0.003    -11.01097    -2.27511
  agrshr20sq |   3.995044   1.603101     2.49   0.013      .853023    7.137065
    agrshr30 |  -1.785593   3.605435    -0.50   0.620    -8.852115     5.28093
  agrshr30sq |   1.083973   2.262763     0.48   0.632    -3.350961    5.518906
  manufshr20 |  -1.584836   2.303865    -0.69   0.492    -6.100327    2.930656
  manufshr30 |   -4.58527   1.905166    -2.41   0.016    -8.319327   -.8512136
 nowage20dum |          0  (omitted)
 nowage30dum |   .4297995   1.932845     0.22   0.824    -3.358508    4.218107
    lnwage20 |  -1.137493   .6994541    -1.63   0.104    -2.508397    .2334122
    lnwage30 |   .3057595   .7551269     0.40   0.686    -1.174262    1.785781
notwage30dum |  -2.150037   2.188879    -0.98   0.326     -6.44016    2.140087
   lntwage30 |  -.7712123   .8064817    -0.96   0.339    -2.351887    .8094628
     lnemp20 |   .7961852   .8657649     0.92   0.358    -.9006828    2.493053
     lnemp30 |   6.348907   2.634326     2.41   0.016     1.185722    11.51209
  urbshare20 |  -3.621274   3.861574    -0.94   0.348    -11.18982    3.947271
  urbshare30 |   4.283208   3.161235     1.35   0.175    -1.912699    10.47912
   lnfaval20 |   -.863291   .7932583    -1.09   0.276    -2.418049    .6914667
   lnfaval30 |   .1773649   1.176538     0.15   0.880    -2.128607    2.483336
lnmedhsval30 |    -2.5812   .7187127    -3.59   0.000     -3.98985   -1.172549
  lnmedrnt30 |   3.003882   .6621823     4.54   0.000     1.706029    4.301736
     white20 |   52.29658   21.73858     2.41   0.016     9.689758    94.90341
   white20sq |  -44.07799   22.19669    -1.99   0.047     -87.5827   -.5732728
     white30 |  -53.47104   20.81156    -2.57   0.010    -94.26094   -12.68113
   white30sq |   46.69502    21.6565     2.16   0.031     4.249058    89.14098
     pctil20 |   .1313362    5.59845     0.02   0.981    -10.84143     11.1041
     pctil30 |   1.597235   10.41263     0.15   0.878    -18.81115    22.00562
    PRADIO30 |  -14.64703   4.657869    -3.14   0.002    -23.77628   -5.517773
     urate30 |  -53.09667   23.83091    -2.23   0.026     -99.8044   -6.388938
     fbshr20 |  -60.78523   58.94046    -1.03   0.302    -176.3064    54.73596
     fbshr30 |  -211.6445   122.3198    -1.73   0.084     -451.387    28.09797
       _cons |   91.87177   24.24085     3.79   0.000     44.36059     139.383
------------------------------------------------------------------------------
Note: 1090 failures and 0 successes completely determined.

. predict phat
(option pr assumed; Pr(tva))
(183 missing values generated)

. 
. keep if e(sample)==1
(183 observations deleted)

. 
. sum phat if tva==1, det

                           Pr(tva)
-------------------------------------------------------------
      Percentiles      Smallest
 1%       .02457       .0188506
 5%        .0733         .02457
10%     .1317301        .028003       Obs                 163
25%     .2763618       .0402206       Sum of Wgt.         163

50%     .5033334                      Mean           .4963477
                        Largest       Std. Dev.      .2691322
75%     .7235231       .9480265
90%     .8653018       .9553998       Variance       .0724322
95%     .9294564       .9735301       Skewness       .0784192
99%     .9735301       .9893857       Kurtosis        1.90468

. sum phat if tva==0, det

                           Pr(tva)
-------------------------------------------------------------
      Percentiles      Smallest
 1%     1.61e-31              0
 5%     2.04e-25              0
10%     2.76e-21              0       Obs                2326
25%     1.47e-15       1.18e-36       Sum of Wgt.        2326

50%     1.91e-07                      Mean           .0352946
                        Largest       Std. Dev.      .1079511
75%     .0052954       .8073446
90%     .0986937       .8148664       Variance       .0116534
95%     .2408053       .8286063       Skewness       4.296825
99%       .58255        .933342       Kurtosis       23.60986

. local cut=r(p25)

. 
. tab tva

        tva |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |      2,326       93.45       93.45
          1 |        163        6.55      100.00
------------+-----------------------------------
      Total |      2,489      100.00

. 
. 
. 
. gen w=pop50 //weights

. 
. 
. drop if phat<`cut'
(582 observations deleted)

. 
. 
. *****************************************
. *****************************************
. *       Reshape Data
. *****************************************
. *****************************************
. tab region, gen(regdum)

     region |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |         98        5.14        5.14
          2 |        695       36.44       41.58
          3 |        942       49.40       90.98
          4 |        172        9.02      100.00
------------+-----------------------------------
      Total |      1,907      100.00

. 
. foreach yr in 20 30 40 50 60 70 80 90 2000{
  2.         cap gen agrdens`yr'=agr`yr'/b1_lnd01_county00
  3.         cap gen lnagrdens`yr'=ln(agrdens`yr')
  4.         gen manufdens`yr'=manuf`yr'/b1_lnd01_county00
  5.         gen lnmanufdens`yr'=ln(manuf`yr'/b1_lnd01_county00)
  6. }
(339 missing values generated)
(230 missing values generated)
(3 missing values generated)
(1 missing value generated)
(1 missing value generated)
(1 missing value generated)
(1 missing value generated)

. 
. *quantile knots for spline components
. local knots "60 85" 

. *local knots "33 66" //uncomment for alternate knots
. 
. centile manufdens80, c(`knots')

                                                       -- Binom. Interp. --
    Variable |     Obs  Percentile      Centile        [95% Conf. Interval]
-------------+-------------------------------------------------------------
 manufdens80 |    1906         60       5.25996        4.889826    5.735682
             |                 85      15.48382        14.12641    16.54906

. local cut1=r(c_1)

. local cut2=r(c_2)

. 
. mkspline manufdens30_1 `cut1' manufdens30_2 `cut2' manufdens30_3 = manufdens3
> 0

. mkspline manufdens40_1 `cut1' manufdens40_2 `cut2' manufdens40_3 = manufdens4
> 0

. mkspline manufdens50_1 `cut1' manufdens50_2 `cut2' manufdens50_3 = manufdens5
> 0

. mkspline manufdens60_1 `cut1' manufdens60_2 `cut2' manufdens60_3 = manufdens6
> 0

. mkspline manufdens70_1 `cut1' manufdens70_2 `cut2' manufdens70_3 = manufdens7
> 0

. mkspline manufdens80_1 `cut1' manufdens80_2 `cut2' manufdens80_3 = manufdens8
> 0

. mkspline manufdens90_1 `cut1' manufdens90_2 `cut2' manufdens90_3 = manufdens9
> 0

. 
. centile lnmanufdens80, c(`knots')

                                                       -- Binom. Interp. --
    Variable |     Obs  Percentile      Centile        [95% Conf. Interval]
-------------+-------------------------------------------------------------
lnmanufde~80 |    1906         60      1.660123        1.587157    1.746706
             |                 85      2.739796        2.648043    2.806329

. local cut1=r(c_1)

. local cut2=r(c_2)

. 
. mkspline lnmanufdens30_1 `cut1' lnmanufdens30_2 `cut2' lnmanufdens30_3 = lnma
> nufdens30

. mkspline lnmanufdens40_1 `cut1' lnmanufdens40_2 `cut2' lnmanufdens40_3 = lnma
> nufdens40

. mkspline lnmanufdens50_1 `cut1' lnmanufdens50_2 `cut2' lnmanufdens50_3 = lnma
> nufdens50

. mkspline lnmanufdens60_1 `cut1' lnmanufdens60_2 `cut2' lnmanufdens60_3 = lnma
> nufdens60

. mkspline lnmanufdens70_1 `cut1' lnmanufdens70_2 `cut2' lnmanufdens70_3 = lnma
> nufdens70

. mkspline lnmanufdens80_1 `cut1' lnmanufdens80_2 `cut2' lnmanufdens80_3 = lnma
> nufdens80

. mkspline lnmanufdens90_1 `cut1' lnmanufdens90_2 `cut2' lnmanufdens90_3 = lnma
> nufdens90

. 
. 
. *for graphing
. local thresh1 `cut1'

. local thresh2 `cut2'

. 
. centile lnmanufdens80, c(5 10 15 20 25 30 35 40 45 50)

                                                       -- Binom. Interp. --
    Variable |     Obs  Percentile      Centile        [95% Conf. Interval]
-------------+-------------------------------------------------------------
lnmanufde~80 |    1906          5     -2.343038       -2.712413   -2.165188
             |                 10     -1.316044       -1.516013   -1.003821
             |                 15     -.5514462        -.717638   -.3145287
             |                 20      -.033896       -.1722047    .0985664
             |                 25      .3255391        .1878248    .4046743
             |                 30      .5220329        .4391314    .6211625
             |                 35      .7660652         .663927    .8427373
             |                 40       .967382        .8730056    1.048848
             |                 45      1.168646        1.067627    1.245475
             |                 50      1.328297        1.267181    1.397139

. local cutg5=r(c_1)

. local cutg10=r(c_2)

. local cutg15=r(c_3)

. local cutg20=r(c_4)

. local cutg25=r(c_5)

. local cutg30=r(c_6)

. local cutg35=r(c_7)

. local cutg40=r(c_8)

. local cutg45=r(c_9)

. local cutg50=r(c_10)

. 
. centile lnmanufdens80, c(55 60 65 70 75 80 85 90 95)

                                                       -- Binom. Interp. --
    Variable |     Obs  Percentile      Centile        [95% Conf. Interval]
-------------+-------------------------------------------------------------
lnmanufde~80 |    1906         55      1.491718        1.417213    1.566677
             |                 60      1.660123        1.587157    1.746706
             |                 65       1.86397        1.786509    1.932181
             |                 70      2.026415        1.955719     2.09075
             |                 75      2.212577        2.134849    2.296137
             |                 80      2.460532        2.352689    2.554924
             |                 85      2.739796        2.648043    2.806329
             |                 90      3.056931        2.941266    3.190523
             |                 95      3.587703         3.46416    3.715235

. local cutg55=r(c_1)

. local cutg60=r(c_2)

. local cutg65=r(c_3)

. local cutg70=r(c_4)

. local cutg75=r(c_5)

. local cutg80=r(c_6)

. local cutg85=r(c_7)

. local cutg90=r(c_8)

. local cutg95=r(c_9)

. 
. *make spline terms
. forvalues i=1/3{
  2.         gen lDmanufdens_`i'=manufdens90_`i'-manufdens80_`i'
  3.         gen l2Dmanufdens_`i'=manufdens80_`i'-manufdens70_`i'
  4.         gen l3Dmanufdens_`i'=manufdens70_`i'-manufdens60_`i'
  5.         gen l4Dmanufdens_`i'=manufdens60_`i'-manufdens50_`i'
  6.         gen l5Dmanufdens_`i'=manufdens50_`i'-manufdens40_`i'
  7.         gen l6Dmanufdens_`i'=manufdens40_`i'-manufdens30_`i'
  8. 
.         gen lDlnmanufdens_`i'=lnmanufdens90_`i'-lnmanufdens80_`i'
  9.         gen l2Dlnmanufdens_`i'=lnmanufdens80_`i'-lnmanufdens70_`i'
 10.         gen l3Dlnmanufdens_`i'=lnmanufdens70_`i'-lnmanufdens60_`i'
 11.         gen l4Dlnmanufdens_`i'=lnmanufdens60_`i'-lnmanufdens50_`i'
 12.         gen l5Dlnmanufdens_`i'=lnmanufdens50_`i'-lnmanufdens40_`i'
 13.         gen l6Dlnmanufdens_`i'=lnmanufdens40_`i'-lnmanufdens30_`i'
 14. }
(1 missing value generated)
(1 missing value generated)
(1 missing value generated)
(4 missing values generated)
(3 missing values generated)
(230 missing values generated)
(1 missing value generated)
(1 missing value generated)
(1 missing value generated)
(4 missing values generated)
(3 missing values generated)
(230 missing values generated)
(1 missing value generated)
(1 missing value generated)
(1 missing value generated)
(4 missing values generated)
(3 missing values generated)
(230 missing values generated)

. 
. gen lDmanufdens=manufdens90-manufdens80
(1 missing value generated)

. gen l2Dmanufdens=manufdens80-manufdens70
(1 missing value generated)

. gen l3Dmanufdens=manufdens70-manufdens60

. gen l4Dmanufdens=manufdens60-manufdens50

. gen l5Dmanufdens=manufdens50-manufdens40

. gen l6Dmanufdens=manufdens40-manufdens30

. 
. gen lDlnmanufdens=lnmanufdens90-lnmanufdens80
(1 missing value generated)

. gen l2Dlnmanufdens=lnmanufdens80-lnmanufdens70
(4 missing values generated)

. gen l3Dlnmanufdens=lnmanufdens70-lnmanufdens60
(3 missing values generated)

. gen l4Dlnmanufdens=lnmanufdens60-lnmanufdens50

. gen l5Dlnmanufdens=lnmanufdens50-lnmanufdens40

. gen l6Dlnmanufdens=lnmanufdens40-lnmanufdens30
(230 missing values generated)

. 
. 
. 
. 
. gen D00=lnmanufdens2000-lnmanufdens90
(1 missing value generated)

. gen D90=lnmanufdens90-lnmanufdens80
(1 missing value generated)

. gen D80=lnmanufdens80-lnmanufdens70
(4 missing values generated)

. gen D70=lnmanufdens70-lnmanufdens60
(3 missing values generated)

. gen D60=lnmanufdens60-lnmanufdens50

. gen D50=lnmanufdens50-lnmanufdens40

. 
. 
. gen W00=lnwage2000-lnwage90
(363 missing values generated)

. gen W90=lnwage90-lnwage80
(447 missing values generated)

. gen W80=lnwage80-lnwage70
(441 missing values generated)

. gen W70=lnwage70-lnwage60
(319 missing values generated)

. gen W60=lnwage60-lnwage50
(320 missing values generated)

. gen W50=lnwage50-lnwage40
(320 missing values generated)

. 
. 
. corr D00 D90 D80 D70 D60 D50
(obs=1903)

             |      D00      D90      D80      D70      D60      D50
-------------+------------------------------------------------------
         D00 |   1.0000
         D90 |  -0.0981   1.0000
         D80 |   0.2430   0.0163   1.0000
         D70 |   0.1110   0.0393  -0.0632   1.0000
         D60 |   0.1013   0.1013   0.0683   0.0735   1.0000
         D50 |   0.0236   0.0388   0.0211   0.0305   0.0910   1.0000


. 
. 
. **spline the instrument**
. gen dens82=emp82/b1_lnd01_county00
(322 missing values generated)

. gen dens77=emp77/b1_lnd01_county00
(353 missing values generated)

. gen dens72=emp72/b1_lnd01_county00
(271 missing values generated)

. gen dens67=emp67/b1_lnd01_county00
(284 missing values generated)

. gen dens63=emp63/b1_lnd01_county00
(49 missing values generated)

. gen dens54=emp54/b1_lnd01_county00
(76 missing values generated)

. gen dens58=emp58/b1_lnd01_county00
(62 missing values generated)

. gen dens47=emp47/b1_lnd01_county00
(83 missing values generated)

. 
. 
. centile dens82, c(`knots')

                                                       -- Binom. Interp. --
    Variable |     Obs  Percentile      Centile        [95% Conf. Interval]
-------------+-------------------------------------------------------------
      dens82 |    1585         60      4.482905          4.0129    4.960421
             |                 85      13.63062        12.55359    15.01437

. local cut1=r(c_1)

. local cut2=r(c_2)

. 
. mkspline dens82_1 `cut1' dens82_2 `cut2' dens82_3 = dens82

. mkspline dens77_1 `cut1' dens77_2 `cut2' dens77_3 = dens77

. mkspline dens72_1 `cut1' dens72_2 `cut2' dens72_3 = dens72

. mkspline dens67_1 `cut1' dens67_2 `cut2' dens67_3 = dens67

. mkspline dens63_1 `cut1' dens63_2 `cut2' dens63_3 = dens63

. mkspline dens54_1 `cut1' dens54_2 `cut2' dens54_3 = dens54

. mkspline dens58_1 `cut1' dens58_2 `cut2' dens58_3 = dens58

. mkspline dens47_1 `cut1' dens47_2 `cut2' dens47_3 = dens47

. 
. forvalues i=1/3{
  2.   gen D82_`i'= dens82_`i'-dens72_`i'
  3.   gen D77_`i'= dens77_`i'-dens67_`i'
  4.   gen D72_`i'= dens72_`i'-dens63_`i'
  5.   gen D67_`i'= dens67_`i'-dens58_`i'
  6.   gen D63_`i'= dens63_`i'-dens54_`i'
  7.   gen D54_`i'= dens54_`i'-dens47_`i'
  8. }
(407 missing values generated)
(450 missing values generated)
(279 missing values generated)
(298 missing values generated)
(93 missing values generated)
(123 missing values generated)
(407 missing values generated)
(450 missing values generated)
(279 missing values generated)
(298 missing values generated)
(93 missing values generated)
(123 missing values generated)
(407 missing values generated)
(450 missing values generated)
(279 missing values generated)
(298 missing values generated)
(93 missing values generated)
(123 missing values generated)

. 
. 
. gen lndens82=ln(dens82)
(330 missing values generated)

. gen lndens77=ln(dens77)
(355 missing values generated)

. gen lndens72=ln(dens72)
(340 missing values generated)

. gen lndens67=ln(dens67)
(399 missing values generated)

. gen lndens63=ln(dens63)
(51 missing values generated)

. gen lndens54=ln(dens54)
(79 missing values generated)

. gen lndens58=ln(dens58)
(65 missing values generated)

. gen lndens47=ln(dens47)
(84 missing values generated)

. 
. 
. centile lndens82, c(`knots')

                                                       -- Binom. Interp. --
    Variable |     Obs  Percentile      Centile        [95% Conf. Interval]
-------------+-------------------------------------------------------------
    lndens82 |    1577         60      1.509636           1.399    1.604174
             |                 85      2.624169        2.536592    2.711308

. local cut1=r(c_1)

. local cut2=r(c_2)

. 
. mkspline lndens82_1 `cut1' lndens82_2 `cut2' lndens82_3 = lndens82

. mkspline lndens77_1 `cut1' lndens77_2 `cut2' lndens77_3 = lndens77

. mkspline lndens72_1 `cut1' lndens72_2 `cut2' lndens72_3 = lndens72

. mkspline lndens67_1 `cut1' lndens67_2 `cut2' lndens67_3 = lndens67

. mkspline lndens63_1 `cut1' lndens63_2 `cut2' lndens63_3 = lndens63

. mkspline lndens54_1 `cut1' lndens54_2 `cut2' lndens54_3 = lndens54

. mkspline lndens58_1 `cut1' lndens58_2 `cut2' lndens58_3 = lndens58

. mkspline lndens47_1 `cut1' lndens47_2 `cut2' lndens47_3 = lndens47

. 
. forvalues i=1/3{
  2.   gen LD82_`i'= lndens82_`i'-lndens72_`i'
  3.   gen LD77_`i'= lndens77_`i'-lndens67_`i'
  4.   gen LD72_`i'= lndens72_`i'-lndens63_`i'
  5.   gen LD67_`i'= lndens67_`i'-lndens58_`i'
  6.   gen LD63_`i'= lndens63_`i'-lndens54_`i'
  7.   gen LD54_`i'= lndens54_`i'-lndens47_`i'
  8. }
(432 missing values generated)
(492 missing values generated)
(342 missing values generated)
(402 missing values generated)
(95 missing values generated)
(123 missing values generated)
(432 missing values generated)
(492 missing values generated)
(342 missing values generated)
(402 missing values generated)
(95 missing values generated)
(123 missing values generated)
(432 missing values generated)
(492 missing values generated)
(342 missing values generated)
(402 missing values generated)
(95 missing values generated)
(123 missing values generated)

. 
. 
. 
. **Detour: Get Deltas Before Completing Reshape**
. 
. **Preferred
. *these coefficients come from Table 5
. local b1=0.097

. local b2=0.042

. local b3=0.001

. 
. 
. gen R4060=lnmanuf60-lnmanuf40-`b1'*(manufdens50_1-manufdens30_1)-`b2'*(manufd
> ens50_2-manufdens30_2)-`b3'*(manufdens50_3-manufdens30_3) + 1.5*(lnwage60-lnw
> age40)
(320 missing values generated)

. gen R6080=lnmanuf80-lnmanuf60-`b1'*(manufdens70_1-manufdens50_1)-`b2'*(manufd
> ens70_2-manufdens50_2)-`b3'*(manufdens70_3-manufdens50_3) + 1.5*(lnwage80-lnw
> age60)
(409 missing values generated)

. gen R802000=lnmanuf2000-lnmanuf80-`b1'*(manufdens90_1-manufdens70_1)-`b2'*(ma
> nufdens90_2-manufdens70_2)-`b3'*(manufdens90_3-manufdens70_3) + 1.5*(lnwage20
> 00-lnwage80)
(374 missing values generated)

. 
. 
. ivreg2 R4060 tva $X [aw=pop50], cluster(state) partial($X)
(sum of wgt is     6.2692e+07)
Warning - collinearities detected
Vars dropped:       nowage20dum nowage30dum

OLS estimation
--------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     1587
                                                      F(  1,    42) =     9.76
                                                      Prob > F      =   0.0032
Total (centered) SS     =  344.8470062                Centered R2   =   0.0139
Total (uncentered) SS   =  344.8470062                Uncentered R2 =   0.0139
Residual SS             =  340.0612411                Root MSE      =    .4629

------------------------------------------------------------------------------
             |               Robust
       R4060 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         tva |    .225221   .0704126     3.20   0.001     .0872148    .3632273
------------------------------------------------------------------------------
Included instruments: tva
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 lnwage20 lnwage30 notwage30dum
                      lntwage30 lnemp20 lnemp30 urbshare20 urbshare30 lnfaval20
                      lnfaval30 lnmedhsval30 lnmedrnt30 white20 white20sq
                      white30 white30sq pctil20 pctil30 PRADIO30 urate30 fbshr2
> 0
                      fbshr30
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum nowage30dum
------------------------------------------------------------------------------

. eststo delt50

. ivreg2 R6080 tva $X  [aw=pop50], cluster(state) partial($X)
(sum of wgt is     6.1102e+07)
Warning - collinearities detected
Vars dropped:       nowage20dum

OLS estimation
--------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     1498
                                                      F(  1,    42) =     0.07
                                                      Prob > F      =   0.7962
Total (centered) SS     =  174.8072709                Centered R2   =   0.0001
Total (uncentered) SS   =  174.8072709                Uncentered R2 =   0.0001
Residual SS             =  174.7966032                Root MSE      =    .3416

------------------------------------------------------------------------------
             |               Robust
       R6080 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         tva |  -.0108171   .0406028    -0.27   0.790     -.090397    .0687629
------------------------------------------------------------------------------
Included instruments: tva
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum
------------------------------------------------------------------------------

. eststo delt70

. ivreg2 R802000 tva $X  [aw=pop50], cluster(state) partial($X)
(sum of wgt is     6.1750e+07)
Warning - collinearities detected
Vars dropped:       nowage20dum

OLS estimation
--------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     1533
                                                      F(  1,    42) =     0.01
                                                      Prob > F      =   0.9262
Total (centered) SS     =  174.2764297                Centered R2   =   0.0000
Total (uncentered) SS   =  174.2764297                Uncentered R2 =   0.0000
Residual SS             =  174.2751155                Root MSE      =    .3372

------------------------------------------------------------------------------
             |               Robust
     R802000 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         tva |  -.0037381   .0391309    -0.10   0.924    -.0804333    .0729571
------------------------------------------------------------------------------
Included instruments: tva
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum
------------------------------------------------------------------------------

. eststo delt90

. 
. 
. *These come from Table 6
. 
. local b1=.4430518

. local b2=.4562646

. local b3=.4655453

.  
. gen LR4060=lnmanuf60-lnmanuf40-`b1'*(lnmanufdens50_1-lnmanufdens30_1)-`b2'*(l
> nmanufdens50_2-lnmanufdens30_2)-`b3'*(lnmanufdens50_3-lnmanufdens30_3) + 1.5*
> (lnwage60-lnwage40)
(320 missing values generated)

. gen LR6080=lnmanuf80-lnmanuf60-`b1'*(lnmanufdens70_1-lnmanufdens50_1)-`b2'*(l
> nmanufdens70_2-lnmanufdens50_2)-`b3'*(lnmanufdens70_3-lnmanufdens50_3) + 1.5*
> (lnwage80-lnwage60)
(409 missing values generated)

. gen LR802000=lnmanuf2000-lnmanuf80-`b1'*(lnmanufdens90_1-lnmanufdens70_1)-`b2
> '*(lnmanufdens90_2-lnmanufdens70_2)-`b3'*(lnmanufdens90_3-lnmanufdens70_3) + 
> 1.5*(lnwage2000-lnwage80)
(374 missing values generated)

. 
. ivreg2 LR4060 tva $X  [aw=pop50], cluster(state) partial($X)
(sum of wgt is     6.2692e+07)
Warning - collinearities detected
Vars dropped:       nowage20dum nowage30dum

OLS estimation
--------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     1587
                                                      F(  1,    42) =     4.98
                                                      Prob > F      =   0.0310
Total (centered) SS     =  319.8768717                Centered R2   =   0.0101
Total (uncentered) SS   =  319.8768717                Uncentered R2 =   0.0101
Residual SS             =  316.6371535                Root MSE      =    .4467

------------------------------------------------------------------------------
             |               Robust
      LR4060 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         tva |   .1853049   .0810945     2.29   0.022     .0263627    .3442471
------------------------------------------------------------------------------
Included instruments: tva
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 lnwage20 lnwage30 notwage30dum
                      lntwage30 lnemp20 lnemp30 urbshare20 urbshare30 lnfaval20
                      lnfaval30 lnmedhsval30 lnmedrnt30 white20 white20sq
                      white30 white30sq pctil20 pctil30 PRADIO30 urate30 fbshr2
> 0
                      fbshr30
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum nowage30dum
------------------------------------------------------------------------------

. eststo delt50L

. ivreg2 LR6080 tva $X   [aw=pop50], cluster(state) partial($X)
(sum of wgt is     6.1102e+07)
Warning - collinearities detected
Vars dropped:       nowage20dum

OLS estimation
--------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     1498
                                                      F(  1,    42) =     1.10
                                                      Prob > F      =   0.3006
Total (centered) SS     =  150.3162279                Centered R2   =   0.0008
Total (uncentered) SS   =  150.3162279                Uncentered R2 =   0.0008
Residual SS             =  150.1993578                Root MSE      =    .3166

------------------------------------------------------------------------------
             |               Robust
      LR6080 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         tva |  -.0358037   .0333308    -1.07   0.283    -.1011308    .0295234
------------------------------------------------------------------------------
Included instruments: tva
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum
------------------------------------------------------------------------------

. eststo delt60L

. ivreg2 LR802000 tva $X  [aw=pop50], cluster(state) partial($X)
(sum of wgt is     6.1750e+07)
Warning - collinearities detected
Vars dropped:       nowage20dum

OLS estimation
--------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     1533
                                                      F(  1,    42) =     0.83
                                                      Prob > F      =   0.3687
Total (centered) SS     =  146.0551997                Centered R2   =   0.0007
Total (uncentered) SS   =  146.0551997                Uncentered R2 =   0.0007
Residual SS             =  145.9535902                Root MSE      =    .3086

------------------------------------------------------------------------------
             |               Robust
    LR802000 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         tva |   .0328685   .0353037     0.93   0.352    -.0363254    .1020625
------------------------------------------------------------------------------
Included instruments: tva
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum
------------------------------------------------------------------------------

. eststo delt80L

. 
. esttab delt* using $tables/delts.csv, replace keep(tva) b(3) se(3) star(* 0.1
>  ** 0.05 *** 0.01) mlab(40-60 60-80 80-2000 "40-60 logs" "60-80 logs" "80-200
> 0 logs")
(output written to ~/latex/tables_raw/delts.csv)

. 
. 
. *convert to long form (Pool changes)
. ren D00 D100

. ren W00 W100

. 
. ren D82_1 Z1_100

. ren D82_2 Z2_100

. ren D82_3 Z3_100

. 
. ren D72_1 Z1_90

. ren D72_2 Z2_90

. ren D72_3 Z3_90

. 
. ren D63_1 Z1_80

. ren D63_2 Z2_80

. ren D63_3 Z3_80

. 
. ren D54_1 Z1_70

. ren D54_2 Z2_70

. ren D54_3 Z3_70

. 
. 
. ren LD82_1 LZ1_100

. ren LD82_2 LZ2_100

. ren LD82_3 LZ3_100

. 
. ren LD72_1 LZ1_90

. ren LD72_2 LZ2_90

. ren LD72_3 LZ3_90

. 
. ren LD63_1 LZ1_80

. ren LD63_2 LZ2_80

. ren LD63_3 LZ3_80

. 
. ren LD54_1 LZ1_70

. ren LD54_2 LZ2_70

. ren LD54_3 LZ3_70

. 
. 
. ren lDmanufdens_1 X1_100

. ren lDmanufdens_2 X2_100

. ren lDmanufdens_3 X3_100

. 
. ren l2Dmanufdens_1 X1_90

. ren l2Dmanufdens_2 X2_90

. ren l2Dmanufdens_3 X3_90

. 
. ren l3Dmanufdens_1 X1_80

. ren l3Dmanufdens_2 X2_80

. ren l3Dmanufdens_3 X3_80

. 
. ren l4Dmanufdens_1 X1_70

. ren l4Dmanufdens_2 X2_70

. ren l4Dmanufdens_3 X3_70

. 
. ren l5Dmanufdens_1 X1_60

. ren l5Dmanufdens_2 X2_60

. ren l5Dmanufdens_3 X3_60

. 
. ren l6Dmanufdens_1 X1_50

. ren l6Dmanufdens_2 X2_50

. ren l6Dmanufdens_3 X3_50

. 
. 
. ren lDlnmanufdens_1 LX1_100

. ren lDlnmanufdens_2 LX2_100

. ren lDlnmanufdens_3 LX3_100

. 
. ren l2Dlnmanufdens_1 LX1_90

. ren l2Dlnmanufdens_2 LX2_90

. ren l2Dlnmanufdens_3 LX3_90

. 
. ren l3Dlnmanufdens_1 LX1_80

. ren l3Dlnmanufdens_2 LX2_80

. ren l3Dlnmanufdens_3 LX3_80

. 
. ren l4Dlnmanufdens_1 LX1_70

. ren l4Dlnmanufdens_2 LX2_70

. ren l4Dlnmanufdens_3 LX3_70

. 
. ren l5Dlnmanufdens_1 LX1_60

. ren l5Dlnmanufdens_2 LX2_60

. ren l5Dlnmanufdens_3 LX3_60

. 
. ren l6Dlnmanufdens_1 LX1_50

. ren l6Dlnmanufdens_2 LX2_50

. ren l6Dlnmanufdens_3 LX3_50

. 
. 
. ren lDmanufdens X_100

. ren l2Dmanufdens X_90

. ren l3Dmanufdens X_80

. ren l4Dmanufdens X_70

. ren l5Dmanufdens X_60

. ren l6Dmanufdens X_50

. 
. ren lDlnmanufdens LX_100

. ren l2Dlnmanufdens LX_90

. ren l3Dlnmanufdens LX_80

. ren l4Dlnmanufdens LX_70

. ren l5Dlnmanufdens LX_60

. ren l6Dlnmanufdens LX_50

. 
. *ren lnmanufdens40 lnmanufdens_40
. ren lnmanufdens50 lnmanufdens_50

. ren lnmanufdens60 lnmanufdens_60

. ren lnmanufdens70 lnmanufdens_70

. ren lnmanufdens80 lnmanufdens_80

. ren lnmanufdens90 lnmanufdens_90

. ren lnmanufdens2000 lnmanufdens_100

. 
. keep *Z* W* D100 D90 D80 D70 D60 D50 *X1* *X2* *X3* *X_* fips state region $X
>  lnmanufdens40 pop80 pop50 b1_lnd01_county00 tva lnmanufdens_* L* b1_lnd01_co
> unty00

. drop *67* *77*

. reshape long W Z1_ Z2_ Z3_ LZ1_ LZ2_ LZ3_ D X1_ X2_ X3_ LX1_ LX2_ LX3_ X_ lnm
> anufdens_ LX, i(fips state region lnmanufdens40 pop80 pop50 b1_lnd01_county00
>  tva b1_lnd01_county00) j(t)
(note: j = 50 60 70 80 90 100)
(note: Z1_50 not found)
(note: Z2_50 not found)
(note: Z3_50 not found)
(note: LZ1_50 not found)
(note: LZ2_50 not found)
(note: LZ3_50 not found)
(note: LX50 not found)
(note: Z1_60 not found)
(note: Z2_60 not found)
(note: Z3_60 not found)
(note: LZ1_60 not found)
(note: LZ2_60 not found)
(note: LZ3_60 not found)
(note: LX60 not found)
(note: LX70 not found)
(note: LX80 not found)
(note: LX90 not found)
(note: LX100 not found)

Data                               wide   ->   long
-----------------------------------------------------------------------------
Number of obs.                     1907   ->   11442
Number of variables                 143   ->      77
j variable (6 values)                     ->   t
xij variables:
                       W50 W60 ... W100   ->   W
                 Z1_50 Z1_60 ... Z1_100   ->   Z1_
                 Z2_50 Z2_60 ... Z2_100   ->   Z2_
                 Z3_50 Z3_60 ... Z3_100   ->   Z3_
              LZ1_50 LZ1_60 ... LZ1_100   ->   LZ1_
              LZ2_50 LZ2_60 ... LZ2_100   ->   LZ2_
              LZ3_50 LZ3_60 ... LZ3_100   ->   LZ3_
                       D50 D60 ... D100   ->   D
                 X1_50 X1_60 ... X1_100   ->   X1_
                 X2_50 X2_60 ... X2_100   ->   X2_
                 X3_50 X3_60 ... X3_100   ->   X3_
              LX1_50 LX1_60 ... LX1_100   ->   LX1_
              LX2_50 LX2_60 ... LX2_100   ->   LX2_
              LX3_50 LX3_60 ... LX3_100   ->   LX3_
                    X_50 X_60 ... X_100   ->   X_
lnmanufdens_50 lnmanufdens_60 ... lnmanufdens_100->lnmanufdens_
                    LX50 LX60 ... LX100   ->   LX
-----------------------------------------------------------------------------

. sum

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
        fips |     11442    29187.86    14536.39       1001      56045
       state |     11442    29.09177    14.52976          1         56
      region |     11442    2.622968    .7197857          1          4
lnmanufde~40 |     11442   -.2484111    1.838397  -6.203884   5.249504
       pop80 |     11436    53280.95    115549.3       1513    2409547
-------------+--------------------------------------------------------
       pop50 |     11442     34908.5    58328.27       1573     806701
b1_lnd01_~00 |     11442    822.8626    969.3882         83      13312
         tva |     11442    .0854746    .2795988          0          1
           t |     11442          75      17.079         50        100
     white20 |     11442    .8632929    .1990515   .1055136          1
-------------+--------------------------------------------------------
     white30 |     11442    .8584088     .194054   .1406302          1
    LPOP3020 |     11442    .0422758     .168036       -.59       1.21
      AVESZ3 |     11442    71.50039    68.95335       4.37     752.99
      LAB311 |     11442    .1699004    .3852124          0          2
     WYMN311 |     11442     .148925    .3560301          0          1
-------------+--------------------------------------------------------
    PRADIO30 |     11442    .2406515    .1682781      .0065      .6677
   lnfaval20 |     11442    5.645179    .7756242   2.995732   7.509335
   lnfaval30 |     11442    5.551091    .6944442   2.482908   8.699514
     fbshr20 |     11442    .0416733    .0468942          0   .3961007
     fbshr30 |     11442    .0274298    .0300546          0   .1255242
-------------+--------------------------------------------------------
  manufshr20 |     11442    .1042727    .1129422          0   .6433638
  manufshr30 |     11442    .0796431    .0963791          0   .8617846
    agrshr20 |     11442    .5404399    .2155918          0          1
    agrshr30 |     11442     .497742    .2132936          0          1
     lnpop20 |     11442    9.874355    .7420154   7.589336   13.10964
-------------+--------------------------------------------------------
     lnpop30 |     11442    9.912801    .7844455   7.567346   13.28679
     lnemp20 |     11442    8.803624     .809514   5.713733   12.32091
     lnemp30 |     11442    8.886341    .8179124   6.629363   12.45848
    lnwage20 |     11442    1.513786     .277145   .5253305   2.730856
    lnwage30 |     11442     1.37464    .9366437         -1   2.620676
-------------+--------------------------------------------------------
   lntwage30 |     11442    1.799369    .5907166         -1   2.327758
lnmedhsval30 |     11442    9.494639    .4443034   8.108729   10.95301
  lnmedrnt30 |     11442    8.903337    .4191124   7.851218   10.12615
  urbshare20 |     11442    .1808154    .2136281          0          1
  urbshare30 |     11442    .2341896    .2830823          0   2.514363
-------------+--------------------------------------------------------
 nowage20dum |     11442           0           0          0          0
 nowage30dum |     11442    .1206083    .3256857          0          1
notwage30dum |     11442    .0393288    .1943845          0          1
   lnelevmax |     11442    7.045158    1.080517   2.833213   9.581491
  lnelevrang |     11442    6.329911    1.189838    2.70805   9.578173
-------------+--------------------------------------------------------
      lnarea |     11442    6.452673     .629754    4.41884   9.499347
   white20sq |     11442    .7848927    .2841412   .0111331          1
   white30sq |     11442    .7745194    .2804547   .0197768          1
   lnpop20sq |     11442    98.05343    14.86117   57.59802   171.8626
   lnpop30sq |     11442    98.87893    15.91327   57.26472   176.5387
-------------+--------------------------------------------------------
    popdifsq |     11442    .0297395    .0784532   1.18e-09   1.457468
  agrshr30sq |     11442    .2932373    .2083667          0          1
  agrshr20sq |     11442    .3385511    .2239455          0          1
     pctil20 |     11442    .0709242    .0773617   .0017432   .5655269
     pctil30 |     11442    .0545316    .0584918   .0004784    .502906
-------------+--------------------------------------------------------
     urate30 |     11442    .0243837     .017352   .0002125   .1121961
lnmanufdens_ |     11437    .8221695    1.802084  -6.772831   5.631238
         X1_ |     11440    .3294273     .628147  -2.687706    5.25996
        LX1_ |     11204    .2573408    .4585688  -2.592983   4.703506
         X2_ |     11440    .3091638     1.06679  -6.644717   10.22386
-------------+--------------------------------------------------------
        LX2_ |     11204    .0361986    .1185044  -.6425532   1.079673
         X3_ |     11440    .3601666    3.585144  -63.26782   66.42171
        LX3_ |     11204    .0120909    .0761301   -.795638   1.154282
          X_ |     11440    .9987577     3.77604  -63.26782   66.42171
      LX_100 |     11436    .0133298    .2762354  -1.519826   2.674149
-------------+--------------------------------------------------------
       LX_90 |     11418    .2631987    .3265826  -1.995491   2.868831
       LX_80 |     11424    .2984027    .3619943  -2.592983   2.144605
       LX_70 |     11442    .3352622    .3913167  -1.504077   3.143294
       LX_60 |     11442      .45624    .4115643   -1.41638   3.704812
       LX_50 |     10062    .4892399    .7311358  -2.110213   4.703506
-------------+--------------------------------------------------------
           D |     11433    .2264146    .3822562  -2.592983   3.704812
           W |      9232    .1426214    .2632296  -1.461817   1.330441
         Z1_ |      6726    .2155478     .599786  -3.125417   4.311853
         Z2_ |      6726    .2375437    1.054969  -5.997031   9.147714
         Z3_ |      6726    .3500614    4.102016  -71.42857   68.25373
-------------+--------------------------------------------------------
        LZ1_ |      6636    .1753654    .5053147  -2.405442   4.109233
        LZ2_ |      6636    .0320642    .1341981  -.6300456   1.114533
        LZ3_ |      6636    .0114354    .0902421  -.6721528    1.37225
      LR4060 |      9522    1.025313     .687126  -1.802939    4.46029
      LR6080 |      8988    .0126917    .4743074  -2.097566   2.056195
-------------+--------------------------------------------------------
    LR802000 |      9198    .7441523     .414844  -.9580033   2.713329
          LX |         0

. 
. 
. 
. tsset fips t, delta(10)
       panel variable:  fips (strongly balanced)
        time variable:  t, 50 to 100
                delta:  10 units

. 
. gen yr90=t==90

. gen yr80=t==80

. gen yr70=t==70

. 
. 
. tab region, gen(regdum)

     region |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |        588        5.14        5.14
          2 |      4,170       36.44       41.58
          3 |      5,652       49.40       90.98
          4 |      1,032        9.02      100.00
------------+-----------------------------------
      Total |     11,442      100.00

. 
. 
. **Calibrated lhs variable
. gen R=D+1.5*W
(2211 missing values generated)

. 
. 
. ***ESTIMATION***
. 
. **spline in levels**
. ivreg2 R X1 X2 X3 yr70 yr80 yr90 $X tva* [w=pop50] if t>=70, cluster(state) p
> artial($X yr70 yr80 yr90) ffirst
(analytic weights assumed)
(sum of wgt is     2.4474e+08)
Warning - collinearities detected
Vars dropped:       nowage20dum

Unable to display summary of first-stage estimates; macro e(first) is missing

OLS estimation
--------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     6057
                                                      F(  4,    42) =    15.54
                                                      Prob > F      =   0.0000
Total (centered) SS     =  487.5080576                Centered R2   =   0.0165
Total (uncentered) SS   =  487.5080576                Uncentered R2 =   0.0165
Residual SS             =  479.4810005                Root MSE      =    .2814

------------------------------------------------------------------------------
             |               Robust
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         X1_ |   .0656136   .0103173     6.36   0.000      .045392    .0858351
         X2_ |   .0207357   .0044648     4.64   0.000     .0119848    .0294866
         X3_ |  -.0000747   .0007393    -0.10   0.919    -.0015237    .0013743
         tva |   .0032587   .0153379     0.21   0.832    -.0268031    .0333204
------------------------------------------------------------------------------
Included instruments: X1_ X2_ X3_ tva
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30 yr70 yr80 yr90
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum
------------------------------------------------------------------------------

. eststo spline1

. test X1=X2=X3

 ( 1)  X1_ - X2_ = 0
 ( 2)  X1_ - X3_ = 0

           chi2(  2) =   48.65
         Prob > chi2 =    0.0000

. estadd scalar equal=r(p)

added scalar:
              e(equal) =  2.724e-11

. test X1 X2 X3

 ( 1)  X1_ = 0
 ( 2)  X2_ = 0
 ( 3)  X3_ = 0

           chi2(  3) =   48.69
         Prob > chi2 =    0.0000

. estadd scalar all=r(p)

added scalar:
                e(all) =  1.515e-10

. 
. ivreg2 R X1 X2 X3 yr70 yr80 yr90 $X tva* lnmanufdens40* [w=pop50] if t>=70, c
> luster(state) partial($X yr70 yr80 yr90 lnmanufdens40*) ffirst
(analytic weights assumed)
(sum of wgt is     2.4474e+08)
Warning - collinearities detected
Vars dropped:       nowage20dum

Unable to display summary of first-stage estimates; macro e(first) is missing

OLS estimation
--------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     6057
                                                      F(  4,    42) =    15.51
                                                      Prob > F      =   0.0000
Total (centered) SS     =  483.6142641                Centered R2   =   0.0157
Total (uncentered) SS   =  483.6142641                Uncentered R2 =   0.0157
Residual SS             =  476.0012959                Root MSE      =    .2803

------------------------------------------------------------------------------
             |               Robust
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         X1_ |   .0603439    .010354     5.83   0.000     .0400504    .0806375
         X2_ |   .0219754   .0043831     5.01   0.000     .0133847    .0305661
         X3_ |   .0000306    .000754     0.04   0.968    -.0014472    .0015084
         tva |   .0080956   .0148163     0.55   0.585    -.0209439     .037135
------------------------------------------------------------------------------
Included instruments: X1_ X2_ X3_ tva
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30 yr70 yr80 yr90
                      lnmanufdens40
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum
------------------------------------------------------------------------------

. eststo spline2

. test X1=X2=X3

 ( 1)  X1_ - X2_ = 0
 ( 2)  X1_ - X3_ = 0

           chi2(  2) =   45.84
         Prob > chi2 =    0.0000

. estadd scalar equal=r(p)

added scalar:
              e(equal) =  1.113e-10

. test X1 X2 X3

 ( 1)  X1_ = 0
 ( 2)  X2_ = 0
 ( 3)  X3_ = 0

           chi2(  3) =   45.90
         Prob > chi2 =    0.0000

. estadd scalar all=r(p)

added scalar:
                e(all) =  5.957e-10

. 
. ivreg2 R X1 X2 X3 yr70 yr80 yr90 $X tva* lnmanufdens40* regdum* [w=pop50] if 
> t>=70, cluster(state) partial($X yr70 yr80 yr90 lnmanufdens40* regdum*) ffirs
> t
(analytic weights assumed)
(sum of wgt is     2.4474e+08)
Warning - collinearities detected
Vars dropped:       nowage20dum regdum4

Unable to display summary of first-stage estimates; macro e(first) is missing

OLS estimation
--------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     6057
                                                      F(  4,    42) =    16.09
                                                      Prob > F      =   0.0000
Total (centered) SS     =  482.1235903                Centered R2   =   0.0157
Total (uncentered) SS   =  482.1235903                Uncentered R2 =   0.0157
Residual SS             =  474.5669722                Root MSE      =    .2799

------------------------------------------------------------------------------
             |               Robust
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         X1_ |   .0599534   .0103129     5.81   0.000     .0397405    .0801663
         X2_ |   .0220028    .004352     5.06   0.000      .013473    .0305326
         X3_ |   -.000112   .0007107    -0.16   0.875    -.0015049    .0012809
         tva |   .0025659   .0150079     0.17   0.864    -.0268491    .0319809
------------------------------------------------------------------------------
Included instruments: X1_ X2_ X3_ tva
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30 yr70 yr80 yr90
                      lnmanufdens40 regdum1 regdum2 regdum3
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum regdum4
------------------------------------------------------------------------------

. eststo spline3

. test X1=X2=X3

 ( 1)  X1_ - X2_ = 0
 ( 2)  X1_ - X3_ = 0

           chi2(  2) =   46.15
         Prob > chi2 =    0.0000

. estadd scalar equal=r(p)

added scalar:
              e(equal) =  9.499e-11

. test X1 X2 X3

 ( 1)  X1_ = 0
 ( 2)  X2_ = 0
 ( 3)  X3_ = 0

           chi2(  3) =   46.32
         Prob > chi2 =    0.0000

. estadd scalar all=r(p)

added scalar:
                e(all) =  4.846e-10

. 
. 
. ivreg2 R (X1 X2 X3 = Z1 Z2 Z3 ) yr70 yr80 yr90 $X tva* [w=pop50] if t>=70, cl
> uster(state) partial($X yr70 yr80 yr90) ffirst
(analytic weights assumed)
(sum of wgt is     2.4294e+08)
Warning - collinearities detected
Vars dropped:       nowage20dum


Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  3,    42)  P-val | AP Chi-sq(  1) P-val | AP F(  1,    42)
X1_          |      89.74    0.0000 |      133.12   0.0000 |      129.06
X2_          |     102.85    0.0000 |      120.54   0.0000 |      116.87
X3_          |      49.86    0.0000 |       43.13   0.0000 |       41.82

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
                                    5% maximal IV relative bias    13.91
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(1)=21.75    P-val=0.0000

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                     195.17
Kleibergen-Paap Wald rk F statistic                                45.73

Stock-Yogo weak ID test critical values for K1=3 and L1=3:
                                                               <not available>
Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(3,42)=        4.34     P-val=0.0094
Anderson-Rubin Wald test           Chi-sq(3)=     13.43     P-val=0.0038
Stock-Wright LM S statistic        Chi-sq(3)=      8.89     P-val=0.0308

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =         43
Number of observations               N  =       5952
Number of regressors                 K  =          4
Number of endogenous regressors      K1 =          3
Number of instruments                L  =          4
Number of excluded instruments       L1 =          3
Number of partialled-out regressors/IVs =         41
NB: K & L do not included partialled-out variables

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     5952
                                                      F(  4,    42) =     4.21
                                                      Prob > F      =   0.0059
Total (centered) SS     =  470.6808591                Centered R2   =   0.0047
Total (uncentered) SS   =  470.6808591                Uncentered R2 =   0.0047
Residual SS             =  468.4832225                Root MSE      =    .2806

------------------------------------------------------------------------------
             |               Robust
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         X1_ |   .0965162   .0374731     2.58   0.010     .0230703     .169962
         X2_ |   .0417808   .0112557     3.71   0.000       .01972    .0638417
         X3_ |    .001881   .0019715     0.95   0.340    -.0019831     .005745
         tva |  -.0051503   .0167931    -0.31   0.759    -.0380643    .0277636
------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             21.750
                                                   Chi-sq(1) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):              195.167
                         (Kleibergen-Paap rk Wald F statistic):         45.727
Stock-Yogo weak ID test critical values:                       <not available>
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         X1_ X2_ X3_
Included instruments: tva
Excluded instruments: Z1_ Z2_ Z3_
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30 yr70 yr80 yr90
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum
------------------------------------------------------------------------------

. eststo spline4

. test X1=X2=X3

 ( 1)  X1_ - X2_ = 0
 ( 2)  X1_ - X3_ = 0

           chi2(  2) =   14.50
         Prob > chi2 =    0.0007

. estadd scalar equal=r(p)

added scalar:
              e(equal) =  .00070968

. test X1 X2 X3

 ( 1)  X1_ = 0
 ( 2)  X2_ = 0
 ( 3)  X3_ = 0

           chi2(  3) =   14.60
         Prob > chi2 =    0.0022

. estadd scalar all=r(p)

added scalar:
                e(all) =  .00218754

. 
. ivreg2 R (X1 X2 X3= Z1 Z2 Z3) yr70 yr80 yr90 $X tva* lnmanufdens40* [w=pop50]
>  if t>=70, cluster(state) partial($X yr70 yr80 yr90 lnmanufdens40*) ffirst
(analytic weights assumed)
(sum of wgt is     2.4294e+08)
Warning - collinearities detected
Vars dropped:       nowage20dum


Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  3,    42)  P-val | AP Chi-sq(  1) P-val | AP F(  1,    42)
X1_          |      84.58    0.0000 |      126.12   0.0000 |      122.25
X2_          |     106.30    0.0000 |      118.50   0.0000 |      114.87
X3_          |      45.80    0.0000 |       42.26   0.0000 |       40.96

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
                                    5% maximal IV relative bias    13.91
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(1)=21.45    P-val=0.0000

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                     192.68
Kleibergen-Paap Wald rk F statistic                                43.31

Stock-Yogo weak ID test critical values for K1=3 and L1=3:
                                                               <not available>
Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(3,42)=        4.81     P-val=0.0057
Anderson-Rubin Wald test           Chi-sq(3)=     14.88     P-val=0.0019
Stock-Wright LM S statistic        Chi-sq(3)=      9.32     P-val=0.0253

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =         43
Number of observations               N  =       5952
Number of regressors                 K  =          4
Number of endogenous regressors      K1 =          3
Number of instruments                L  =          4
Number of excluded instruments       L1 =          3
Number of partialled-out regressors/IVs =         42
NB: K & L do not included partialled-out variables

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     5952
                                                      F(  4,    42) =     4.65
                                                      Prob > F      =   0.0034
Total (centered) SS     =  467.0395302                Centered R2   =   0.0041
Total (uncentered) SS   =  467.0395302                Uncentered R2 =   0.0041
Residual SS             =  465.1159193                Root MSE      =    .2795

------------------------------------------------------------------------------
             |               Robust
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         X1_ |    .084497   .0374458     2.26   0.024     .0111046    .1578894
         X2_ |   .0425543   .0109259     3.89   0.000       .02114    .0639687
         X3_ |   .0021467   .0020114     1.07   0.286    -.0017956    .0060891
         tva |   .0012496   .0163873     0.08   0.939    -.0308689    .0333682
------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             21.453
                                                   Chi-sq(1) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):              192.684
                         (Kleibergen-Paap rk Wald F statistic):         43.314
Stock-Yogo weak ID test critical values:                       <not available>
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         X1_ X2_ X3_
Included instruments: tva
Excluded instruments: Z1_ Z2_ Z3_
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30 yr70 yr80 yr90
                      lnmanufdens40
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum
------------------------------------------------------------------------------

. eststo spline5

. test X1=X2=X3

 ( 1)  X1_ - X2_ = 0
 ( 2)  X1_ - X3_ = 0

           chi2(  2) =   14.84
         Prob > chi2 =    0.0006

. estadd scalar equal=r(p)

added scalar:
              e(equal) =  .00060018

. test X1 X2 X3

 ( 1)  X1_ = 0
 ( 2)  X2_ = 0
 ( 3)  X3_ = 0

           chi2(  3) =   15.40
         Prob > chi2 =    0.0015

. estadd scalar all=r(p)

added scalar:
                e(all) =  .00150661

. 
. ivreg2 R (X1 X2 X3= Z1 Z2 Z3) yr70 yr80 yr90 $X tva* lnmanufdens40* regdum* [
> w=pop50] if t>=70, cluster(state) partial($X yr70 yr80 yr90 lnmanufdens40* re
> gdum*) ffirst
(analytic weights assumed)
(sum of wgt is     2.4294e+08)
Warning - collinearities detected
Vars dropped:       nowage20dum regdum4


Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  3,    42)  P-val | AP Chi-sq(  1) P-val | AP F(  1,    42)
X1_          |      83.56    0.0000 |      124.96   0.0000 |      121.07
X2_          |     107.85    0.0000 |      120.40   0.0000 |      116.66
X3_          |      41.34    0.0000 |       33.06   0.0000 |       32.04

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
                                    5% maximal IV relative bias    13.91
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(1)=21.86    P-val=0.0000

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                     188.51
Kleibergen-Paap Wald rk F statistic                                45.82

Stock-Yogo weak ID test critical values for K1=3 and L1=3:
                                                               <not available>
Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(3,42)=        4.61     P-val=0.0071
Anderson-Rubin Wald test           Chi-sq(3)=     14.28     P-val=0.0025
Stock-Wright LM S statistic        Chi-sq(3)=      9.03     P-val=0.0289

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =         43
Number of observations               N  =       5952
Number of regressors                 K  =          4
Number of endogenous regressors      K1 =          3
Number of instruments                L  =          4
Number of excluded instruments       L1 =          3
Number of partialled-out regressors/IVs =         45
NB: K & L do not included partialled-out variables

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     5952
                                                      F(  4,    42) =     4.29
                                                      Prob > F      =   0.0053
Total (centered) SS     =  465.4980028                Centered R2   =   0.0056
Total (uncentered) SS   =  465.4980028                Uncentered R2 =   0.0056
Residual SS             =  462.8764336                Root MSE      =    .2789

------------------------------------------------------------------------------
             |               Robust
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         X1_ |   .0823344   .0371623     2.22   0.027     .0094976    .1551712
         X2_ |   .0416636    .010844     3.84   0.000     .0204098    .0629174
         X3_ |   .0017838   .0019589     0.91   0.362    -.0020556    .0056233
         tva |  -.0043463   .0162407    -0.27   0.789    -.0361774    .0274849
------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             21.856
                                                   Chi-sq(1) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):              188.507
                         (Kleibergen-Paap rk Wald F statistic):         45.822
Stock-Yogo weak ID test critical values:                       <not available>
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         X1_ X2_ X3_
Included instruments: tva
Excluded instruments: Z1_ Z2_ Z3_
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30 yr70 yr80 yr90
                      lnmanufdens40 regdum1 regdum2 regdum3
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum regdum4
------------------------------------------------------------------------------

. eststo spline6

. test X1=X2=X3

 ( 1)  X1_ - X2_ = 0
 ( 2)  X1_ - X3_ = 0

           chi2(  2) =   14.72
         Prob > chi2 =    0.0006

. estadd scalar equal=r(p)

added scalar:
              e(equal) =  .00063508

. test X1 X2 X3

 ( 1)  X1_ = 0
 ( 2)  X2_ = 0
 ( 3)  X3_ = 0

           chi2(  3) =   14.94
         Prob > chi2 =    0.0019

. estadd scalar all=r(p)

added scalar:
                e(all) =  .00186467

. 
. 
. esttab spline1 spline2 spline3 spline4 spline5 spline6 using $tables/g_tercil
> es_opt.csv, replace cell( b(fmt(a2)) se(par fmt(a2)) first[APF](par([ ]) fmt(
> 2) ) ) stat(equal all N, fmt(%6.0g))
(output written to ~/latex/tables_raw/g_terciles_opt.csv)

. 
. **now in logs**
. ivreg2 R LX1 LX2 LX3 yr70 yr80 yr90 $X tva* [w=pop50] if t>=70, cluster(state
> ) partial($X yr70 yr80 yr90) ffirst
(analytic weights assumed)
(sum of wgt is     2.4474e+08)
Warning - collinearities detected
Vars dropped:       nowage20dum

Unable to display summary of first-stage estimates; macro e(first) is missing

OLS estimation
--------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     6057
                                                      F(  4,    42) =    11.83
                                                      Prob > F      =   0.0000
Total (centered) SS     =  487.5080576                Centered R2   =   0.0191
Total (uncentered) SS   =  487.5080576                Uncentered R2 =   0.0191
Residual SS             =  478.2057145                Root MSE      =     .281

------------------------------------------------------------------------------
             |               Robust
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        LX1_ |   .1730485   .0365409     4.74   0.000     .1014297    .2446674
        LX2_ |   .2209151   .0454047     4.87   0.000     .1319236    .3099066
        LX3_ |   .1433129   .0505371     2.84   0.005      .044262    .2423638
         tva |   .0073418    .014062     0.52   0.602    -.0202193    .0349029
------------------------------------------------------------------------------
Included instruments: LX1_ LX2_ LX3_ tva
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30 yr70 yr80 yr90
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum
------------------------------------------------------------------------------

. eststo spline1

. test LX1=LX2=LX3

 ( 1)  LX1_ - LX2_ = 0
 ( 2)  LX1_ - LX3_ = 0

           chi2(  2) =    2.79
         Prob > chi2 =    0.2483

. estadd scalar equal=r(p)

added scalar:
              e(equal) =  .24828272

. test LX1 LX2 LX3

 ( 1)  LX1_ = 0
 ( 2)  LX2_ = 0
 ( 3)  LX3_ = 0

           chi2(  3) =   34.06
         Prob > chi2 =    0.0000

. estadd scalar all=r(p)

added scalar:
                e(all) =  1.920e-07

. 
. ivreg2 R LX1 LX2 LX3 yr70 yr80 yr90 $X tva* lnmanufdens40* [w=pop50] if t>=70
> , cluster(state) partial($X yr70 yr80 yr90 lnmanufdens40*) ffirst
(analytic weights assumed)
(sum of wgt is     2.4474e+08)
Warning - collinearities detected
Vars dropped:       nowage20dum

Unable to display summary of first-stage estimates; macro e(first) is missing

OLS estimation
--------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     6057
                                                      F(  4,    42) =    11.77
                                                      Prob > F      =   0.0000
Total (centered) SS     =  483.6142641                Centered R2   =   0.0171
Total (uncentered) SS   =  483.6142641                Uncentered R2 =   0.0171
Residual SS             =  475.3408321                Root MSE      =    .2801

------------------------------------------------------------------------------
             |               Robust
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        LX1_ |   .1474953   .0371991     3.97   0.000     .0745864    .2204042
        LX2_ |   .2272859   .0444248     5.12   0.000     .1402148    .3143569
        LX3_ |   .1508999   .0503185     3.00   0.003     .0522774    .2495224
         tva |   .0121904   .0137282     0.89   0.375    -.0147163    .0390972
------------------------------------------------------------------------------
Included instruments: LX1_ LX2_ LX3_ tva
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30 yr70 yr80 yr90
                      lnmanufdens40
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum
------------------------------------------------------------------------------

. eststo spline2

. test LX1=LX2=LX3

 ( 1)  LX1_ - LX2_ = 0
 ( 2)  LX1_ - LX3_ = 0

           chi2(  2) =    4.08
         Prob > chi2 =    0.1298

. estadd scalar equal=r(p)

added scalar:
              e(equal) =  .12982298

. test LX1 LX2 LX3

 ( 1)  LX1_ = 0
 ( 2)  LX2_ = 0
 ( 3)  LX3_ = 0

           chi2(  3) =   32.04
         Prob > chi2 =    0.0000

. estadd scalar all=r(p)

added scalar:
                e(all) =  5.127e-07

. 
. ivreg2 R LX1 LX2 LX3 yr70 yr80 yr90 $X tva* lnmanufdens40* regdum* [w=pop50] 
> if t>=70, cluster(state) partial($X yr70 yr80 yr90 lnmanufdens40* regdum*) ff
> irst
(analytic weights assumed)
(sum of wgt is     2.4474e+08)
Warning - collinearities detected
Vars dropped:       nowage20dum regdum4

Unable to display summary of first-stage estimates; macro e(first) is missing

OLS estimation
--------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     6057
                                                      F(  4,    42) =    10.99
                                                      Prob > F      =   0.0000
Total (centered) SS     =  482.1235903                Centered R2   =   0.0163
Total (uncentered) SS   =  482.1235903                Uncentered R2 =   0.0163
Residual SS             =  474.2681662                Root MSE      =    .2798

------------------------------------------------------------------------------
             |               Robust
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        LX1_ |   .1455718   .0371143     3.92   0.000     .0728291    .2183145
        LX2_ |   .2258517    .044501     5.08   0.000     .1386313     .313072
        LX3_ |   .1409434   .0502112     2.81   0.005     .0425312    .2393557
         tva |   .0075613   .0138703     0.55   0.586     -.019624    .0347465
------------------------------------------------------------------------------
Included instruments: LX1_ LX2_ LX3_ tva
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30 yr70 yr80 yr90
                      lnmanufdens40 regdum1 regdum2 regdum3
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum regdum4
------------------------------------------------------------------------------

. eststo spline3

. test LX1=LX2=LX3

 ( 1)  LX1_ - LX2_ = 0
 ( 2)  LX1_ - LX3_ = 0

           chi2(  2) =    4.53
         Prob > chi2 =    0.1038

. estadd scalar equal=r(p)

added scalar:
              e(equal) =  .10378423

. test LX1 LX2 LX3

 ( 1)  LX1_ = 0
 ( 2)  LX2_ = 0
 ( 3)  LX3_ = 0

           chi2(  3) =   31.44
         Prob > chi2 =    0.0000

. estadd scalar all=r(p)

added scalar:
                e(all) =  6.866e-07

. 
. 
. ivreg2 R (LX1 LX2 LX3 = LZ1 LZ2 LZ3 ) yr70 yr80 yr90 $X tva* [w=pop50] if t>=
> 70, cluster(state) partial($X yr70 yr80 yr90) ffirst
(analytic weights assumed)
(sum of wgt is     2.4278e+08)
Warning - collinearities detected
Vars dropped:       nowage20dum


Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  3,    42)  P-val | AP Chi-sq(  1) P-val | AP F(  1,    42)
LX1_         |      96.94    0.0000 |      182.75   0.0000 |      177.17
LX2_         |      52.14    0.0000 |      110.10   0.0000 |      106.74
LX3_         |      90.79    0.0000 |      213.16   0.0000 |      206.66

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
                                    5% maximal IV relative bias    13.91
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(1)=21.25    P-val=0.0000

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                     151.08
Kleibergen-Paap Wald rk F statistic                                68.10

Stock-Yogo weak ID test critical values for K1=3 and L1=3:
                                                               <not available>
Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(3,42)=        7.04     P-val=0.0006
Anderson-Rubin Wald test           Chi-sq(3)=     21.77     P-val=0.0001
Stock-Wright LM S statistic        Chi-sq(3)=     14.22     P-val=0.0026

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =         43
Number of observations               N  =       5935
Number of regressors                 K  =          4
Number of endogenous regressors      K1 =          3
Number of instruments                L  =          4
Number of excluded instruments       L1 =          3
Number of partialled-out regressors/IVs =         41
NB: K & L do not included partialled-out variables

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     5935
                                                      F(  4,    42) =     6.89
                                                      Prob > F      =   0.0002
Total (centered) SS     =  468.1628927                Centered R2   =  -0.0252
Total (uncentered) SS   =  468.1628927                Uncentered R2 =  -0.0252
Residual SS             =  479.9839614                Root MSE      =    .2844

------------------------------------------------------------------------------
             |               Robust
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        LX1_ |   .4430518   .1016244     4.36   0.000     .2438716    .6422319
        LX2_ |   .4562646   .1236878     3.69   0.000      .213841    .6986882
        LX3_ |   .4655453   .1502765     3.10   0.002     .1710087    .7600818
         tva |  -.0029331   .0121575    -0.24   0.809    -.0267615    .0208952
------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             21.245
                                                   Chi-sq(1) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):              151.076
                         (Kleibergen-Paap rk Wald F statistic):         68.100
Stock-Yogo weak ID test critical values:                       <not available>
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         LX1_ LX2_ LX3_
Included instruments: tva
Excluded instruments: LZ1_ LZ2_ LZ3_
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30 yr70 yr80 yr90
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum
------------------------------------------------------------------------------

. eststo spline4

. test LX1=LX2=LX3

 ( 1)  LX1_ - LX2_ = 0
 ( 2)  LX1_ - LX3_ = 0

           chi2(  2) =    0.09
         Prob > chi2 =    0.9545

. estadd scalar equal=r(p)

added scalar:
              e(equal) =  .95450299

. test LX1 LX2 LX3

 ( 1)  LX1_ = 0
 ( 2)  LX2_ = 0
 ( 3)  LX3_ = 0

           chi2(  3) =   20.29
         Prob > chi2 =    0.0001

. estadd scalar all=r(p)

added scalar:
                e(all) =  .00014757

. 
. ivreg2 R (LX1 LX2 LX3= LZ1 LZ2 LZ3) yr70 yr80 yr90 $X tva* lnmanufdens40* [w=
> pop50] if t>=70, cluster(state) partial($X yr70 yr80 yr90 lnmanufdens40*) ffi
> rst
(analytic weights assumed)
(sum of wgt is     2.4278e+08)
Warning - collinearities detected
Vars dropped:       nowage20dum


Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  3,    42)  P-val | AP Chi-sq(  1) P-val | AP F(  1,    42)
LX1_         |      81.49    0.0000 |      164.18   0.0000 |      159.14
LX2_         |      52.20    0.0000 |      113.01   0.0000 |      109.55
LX3_         |      82.01    0.0000 |      211.17   0.0000 |      204.69

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
                                    5% maximal IV relative bias    13.91
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(1)=20.67    P-val=0.0000

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                     133.18
Kleibergen-Paap Wald rk F statistic                                56.06

Stock-Yogo weak ID test critical values for K1=3 and L1=3:
                                                               <not available>
Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(3,42)=        5.90     P-val=0.0019
Anderson-Rubin Wald test           Chi-sq(3)=     18.27     P-val=0.0004
Stock-Wright LM S statistic        Chi-sq(3)=     13.06     P-val=0.0045

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =         43
Number of observations               N  =       5935
Number of regressors                 K  =          4
Number of endogenous regressors      K1 =          3
Number of instruments                L  =          4
Number of excluded instruments       L1 =          3
Number of partialled-out regressors/IVs =         42
NB: K & L do not included partialled-out variables

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     5935
                                                      F(  4,    42) =     6.48
                                                      Prob > F      =   0.0004
Total (centered) SS     =  464.6310716                Centered R2   =  -0.0221
Total (uncentered) SS   =  464.6310716                Uncentered R2 =  -0.0221
Residual SS             =  474.9214068                Root MSE      =    .2829

------------------------------------------------------------------------------
             |               Robust
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        LX1_ |   .4001675   .1076074     3.72   0.000     .1892609    .6110741
        LX2_ |   .4396976   .1233138     3.57   0.000      .198007    .6813881
        LX3_ |    .466872   .1500048     3.11   0.002     .1728681    .7608759
         tva |   .0020741   .0125531     0.17   0.869    -.0225296    .0266778
------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             20.667
                                                   Chi-sq(1) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):              133.179
                         (Kleibergen-Paap rk Wald F statistic):         56.060
Stock-Yogo weak ID test critical values:                       <not available>
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         LX1_ LX2_ LX3_
Included instruments: tva
Excluded instruments: LZ1_ LZ2_ LZ3_
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30 yr70 yr80 yr90
                      lnmanufdens40
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum
------------------------------------------------------------------------------

. eststo spline5

. test LX1=LX2=LX3

 ( 1)  LX1_ - LX2_ = 0
 ( 2)  LX1_ - LX3_ = 0

           chi2(  2) =    0.80
         Prob > chi2 =    0.6690

. estadd scalar equal=r(p)

added scalar:
              e(equal) =  .66899965

. test LX1 LX2 LX3

 ( 1)  LX1_ = 0
 ( 2)  LX2_ = 0
 ( 3)  LX3_ = 0

           chi2(  3) =   16.90
         Prob > chi2 =    0.0007

. estadd scalar all=r(p)

added scalar:
                e(all) =  .0007427

. 
. ivreg2 R (LX1 LX2 LX3= LZ1 LZ2 LZ3) yr70 yr80 yr90 $X tva* lnmanufdens40* reg
> dum* [w=pop50] if t>=70, cluster(state) partial($X yr70 yr80 yr90 lnmanufdens
> 40* regdum*) ffirst
(analytic weights assumed)
(sum of wgt is     2.4278e+08)
Warning - collinearities detected
Vars dropped:       nowage20dum regdum4


Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  3,    42)  P-val | AP Chi-sq(  1) P-val | AP F(  1,    42)
LX1_         |      82.39    0.0000 |      162.25   0.0000 |      157.20
LX2_         |      54.89    0.0000 |      113.67   0.0000 |      110.13
LX3_         |      84.55    0.0000 |      206.81   0.0000 |      200.36

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
                                    5% maximal IV relative bias    13.91
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(1)=20.66    P-val=0.0000

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                     131.85
Kleibergen-Paap Wald rk F statistic                                55.96

Stock-Yogo weak ID test critical values for K1=3 and L1=3:
                                                               <not available>
Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(3,42)=        5.82     P-val=0.0020
Anderson-Rubin Wald test           Chi-sq(3)=     18.03     P-val=0.0004
Stock-Wright LM S statistic        Chi-sq(3)=     13.10     P-val=0.0044

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =         43
Number of observations               N  =       5935
Number of regressors                 K  =          4
Number of endogenous regressors      K1 =          3
Number of instruments                L  =          4
Number of excluded instruments       L1 =          3
Number of partialled-out regressors/IVs =         45
NB: K & L do not included partialled-out variables

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     5935
                                                      F(  4,    42) =     5.84
                                                      Prob > F      =   0.0008
Total (centered) SS     =  463.1182604                Centered R2   =  -0.0221
Total (uncentered) SS   =  463.1182604                Uncentered R2 =  -0.0221
Residual SS             =  473.3353884                Root MSE      =    .2824

------------------------------------------------------------------------------
             |               Robust
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        LX1_ |   .3956912   .1072537     3.69   0.000     .1854777    .6059046
        LX2_ |   .4376415   .1242672     3.52   0.000     .1940822    .6812008
        LX3_ |   .4528073   .1510502     3.00   0.003     .1567543    .7488603
         tva |  -.0023732   .0123403    -0.19   0.847    -.0265597    .0218133
------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             20.660
                                                   Chi-sq(1) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):              131.850
                         (Kleibergen-Paap rk Wald F statistic):         55.955
Stock-Yogo weak ID test critical values:                       <not available>
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         LX1_ LX2_ LX3_
Included instruments: tva
Excluded instruments: LZ1_ LZ2_ LZ3_
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30 yr70 yr80 yr90
                      lnmanufdens40 regdum1 regdum2 regdum3
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum regdum4
------------------------------------------------------------------------------

. eststo spline6

. test LX1=LX2=LX3

 ( 1)  LX1_ - LX2_ = 0
 ( 2)  LX1_ - LX3_ = 0

           chi2(  2) =    0.66
         Prob > chi2 =    0.7171

. estadd scalar equal=r(p)

added scalar:
              e(equal) =  .7171471

. test LX1 LX2 LX3

 ( 1)  LX1_ = 0
 ( 2)  LX2_ = 0
 ( 3)  LX3_ = 0

           chi2(  3) =   16.24
         Prob > chi2 =    0.0010

. estadd scalar all=r(p)

added scalar:
                e(all) =  .00101187

. 
. 
. esttab spline1 spline2 spline3 spline4 spline5 spline6 using $tables/g_tercil
> es_opt_logs.csv, replace cell( b(fmt(3)) se(par fmt(3)) first[APF](par([ ]) f
> mt(2) ) ) stat(equal all N, fmt(%6.0g))
(output written to ~/latex/tables_raw/g_terciles_opt_logs.csv)

. 
. 
. **sensitivity**
. gen R1=D+W
(2211 missing values generated)

. gen R2=D+2*W
(2211 missing values generated)

. 
. ivreg2 R1 (X1 X2 X3 = Z1 Z2 Z3 ) yr70 yr80 yr90 $X tva* [w=pop50] if t>=70, c
> luster(state) partial($X yr70 yr80 yr90) ffirst
(analytic weights assumed)
(sum of wgt is     2.4294e+08)
Warning - collinearities detected
Vars dropped:       nowage20dum


Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  3,    42)  P-val | AP Chi-sq(  1) P-val | AP F(  1,    42)
X1_          |      89.74    0.0000 |      133.12   0.0000 |      129.06
X2_          |     102.85    0.0000 |      120.54   0.0000 |      116.87
X3_          |      49.86    0.0000 |       43.13   0.0000 |       41.82

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
                                    5% maximal IV relative bias    13.91
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(1)=21.75    P-val=0.0000

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                     195.17
Kleibergen-Paap Wald rk F statistic                                45.73

Stock-Yogo weak ID test critical values for K1=3 and L1=3:
                                                               <not available>
Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(3,42)=        4.59     P-val=0.0072
Anderson-Rubin Wald test           Chi-sq(3)=     14.22     P-val=0.0026
Stock-Wright LM S statistic        Chi-sq(3)=      9.20     P-val=0.0267

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =         43
Number of observations               N  =       5952
Number of regressors                 K  =          4
Number of endogenous regressors      K1 =          3
Number of instruments                L  =          4
Number of excluded instruments       L1 =          3
Number of partialled-out regressors/IVs =         41
NB: K & L do not included partialled-out variables

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     5952
                                                      F(  4,    42) =     4.62
                                                      Prob > F      =   0.0035
Total (centered) SS     =  332.9948961                Centered R2   =   0.0035
Total (uncentered) SS   =  332.9948961                Uncentered R2 =   0.0035
Residual SS             =  331.8276649                Root MSE      =    .2361

------------------------------------------------------------------------------
             |               Robust
          R1 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         X1_ |   .0839457   .0312759     2.68   0.007     .0226461    .1452454
         X2_ |   .0349862    .009263     3.78   0.000     .0168311    .0531414
         X3_ |   .0013565   .0015592     0.87   0.384    -.0016995    .0044124
         tva |  -.0030385   .0150615    -0.20   0.840    -.0325585    .0264816
------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             21.750
                                                   Chi-sq(1) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):              195.167
                         (Kleibergen-Paap rk Wald F statistic):         45.727
Stock-Yogo weak ID test critical values:                       <not available>
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         X1_ X2_ X3_
Included instruments: tva
Excluded instruments: Z1_ Z2_ Z3_
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30 yr70 yr80 yr90
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum
------------------------------------------------------------------------------

. eststo spline1

. test X1=X2=X3

 ( 1)  X1_ - X2_ = 0
 ( 2)  X1_ - X3_ = 0

           chi2(  2) =   15.66
         Prob > chi2 =    0.0004

. estadd scalar equal=r(p)

added scalar:
              e(equal) =  .00039794

. test X1 X2 X3

 ( 1)  X1_ = 0
 ( 2)  X2_ = 0
 ( 3)  X3_ = 0

           chi2(  3) =   15.66
         Prob > chi2 =    0.0013

. estadd scalar all=r(p)

added scalar:
                e(all) =  .00132833

. 
. ivreg2 R1 (X1 X2 X3 = Z1 Z2 Z3 ) yr70 yr80 yr90 $X tva* lnmanufdens40* [w=pop
> 50] if t>=70, cluster(state) partial($X yr70 yr80 yr90 lnmanufdens40*) ffirst
(analytic weights assumed)
(sum of wgt is     2.4294e+08)
Warning - collinearities detected
Vars dropped:       nowage20dum


Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  3,    42)  P-val | AP Chi-sq(  1) P-val | AP F(  1,    42)
X1_          |      84.58    0.0000 |      126.12   0.0000 |      122.25
X2_          |     106.30    0.0000 |      118.50   0.0000 |      114.87
X3_          |      45.80    0.0000 |       42.26   0.0000 |       40.96

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
                                    5% maximal IV relative bias    13.91
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(1)=21.45    P-val=0.0000

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                     192.68
Kleibergen-Paap Wald rk F statistic                                43.31

Stock-Yogo weak ID test critical values for K1=3 and L1=3:
                                                               <not available>
Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(3,42)=        5.00     P-val=0.0047
Anderson-Rubin Wald test           Chi-sq(3)=     15.47     P-val=0.0015
Stock-Wright LM S statistic        Chi-sq(3)=      9.54     P-val=0.0229

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =         43
Number of observations               N  =       5952
Number of regressors                 K  =          4
Number of endogenous regressors      K1 =          3
Number of instruments                L  =          4
Number of excluded instruments       L1 =          3
Number of partialled-out regressors/IVs =         42
NB: K & L do not included partialled-out variables

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     5952
                                                      F(  4,    42) =     5.04
                                                      Prob > F      =   0.0021
Total (centered) SS     =  329.8374187                Centered R2   =   0.0033
Total (uncentered) SS   =  329.8374187                Uncentered R2 =   0.0033
Residual SS             =  328.7406052                Root MSE      =     .235

------------------------------------------------------------------------------
             |               Robust
          R1 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         X1_ |   .0728679   .0313896     2.32   0.020     .0113453    .1343904
         X2_ |   .0356992   .0089985     3.97   0.000     .0180623     .053336
         X3_ |   .0016014   .0015883     1.01   0.313    -.0015116    .0047145
         tva |   .0028602   .0147012     0.19   0.846    -.0259535     .031674
------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             21.453
                                                   Chi-sq(1) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):              192.684
                         (Kleibergen-Paap rk Wald F statistic):         43.314
Stock-Yogo weak ID test critical values:                       <not available>
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         X1_ X2_ X3_
Included instruments: tva
Excluded instruments: Z1_ Z2_ Z3_
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30 yr70 yr80 yr90
                      lnmanufdens40
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum
------------------------------------------------------------------------------

. eststo spline2

. test X1=X2=X3

 ( 1)  X1_ - X2_ = 0
 ( 2)  X1_ - X3_ = 0

           chi2(  2) =   15.90
         Prob > chi2 =    0.0004

. estadd scalar equal=r(p)

added scalar:
              e(equal) =  .00035238

. test X1 X2 X3

 ( 1)  X1_ = 0
 ( 2)  X2_ = 0
 ( 3)  X3_ = 0

           chi2(  3) =   16.06
         Prob > chi2 =    0.0011

. estadd scalar all=r(p)

added scalar:
                e(all) =  .00110011

. 
. ivreg2 R1 (X1 X2 X3 = Z1 Z2 Z3 ) yr70 yr80 yr90 $X tva* lnmanufdens40* regdum
> * [w=pop50] if t>=70, cluster(state) partial($X yr70 yr80 yr90 lnmanufdens40*
>  regdum*) ffirst
(analytic weights assumed)
(sum of wgt is     2.4294e+08)
Warning - collinearities detected
Vars dropped:       nowage20dum regdum4


Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  3,    42)  P-val | AP Chi-sq(  1) P-val | AP F(  1,    42)
X1_          |      83.56    0.0000 |      124.96   0.0000 |      121.07
X2_          |     107.85    0.0000 |      120.40   0.0000 |      116.66
X3_          |      41.34    0.0000 |       33.06   0.0000 |       32.04

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
                                    5% maximal IV relative bias    13.91
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(1)=21.86    P-val=0.0000

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                     188.51
Kleibergen-Paap Wald rk F statistic                                45.82

Stock-Yogo weak ID test critical values for K1=3 and L1=3:
                                                               <not available>
Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(3,42)=        4.79     P-val=0.0059
Anderson-Rubin Wald test           Chi-sq(3)=     14.83     P-val=0.0020
Stock-Wright LM S statistic        Chi-sq(3)=      9.18     P-val=0.0270

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =         43
Number of observations               N  =       5952
Number of regressors                 K  =          4
Number of endogenous regressors      K1 =          3
Number of instruments                L  =          4
Number of excluded instruments       L1 =          3
Number of partialled-out regressors/IVs =         45
NB: K & L do not included partialled-out variables

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     5952
                                                      F(  4,    42) =     4.66
                                                      Prob > F      =   0.0034
Total (centered) SS     =  328.7251394                Centered R2   =   0.0047
Total (uncentered) SS   =  328.7251394                Uncentered R2 =   0.0047
Residual SS             =  327.1799114                Root MSE      =    .2345

------------------------------------------------------------------------------
             |               Robust
          R1 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         X1_ |   .0710666   .0311244     2.28   0.022     .0100639    .1320694
         X2_ |    .034722   .0089286     3.89   0.000     .0172224    .0522217
         X3_ |    .001312   .0015529     0.84   0.398    -.0017316    .0043556
         tva |  -.0013103    .014941    -0.09   0.930    -.0305941    .0279736
------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             21.856
                                                   Chi-sq(1) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):              188.507
                         (Kleibergen-Paap rk Wald F statistic):         45.822
Stock-Yogo weak ID test critical values:                       <not available>
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         X1_ X2_ X3_
Included instruments: tva
Excluded instruments: Z1_ Z2_ Z3_
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30 yr70 yr80 yr90
                      lnmanufdens40 regdum1 regdum2 regdum3
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum regdum4
------------------------------------------------------------------------------

. eststo spline3

. test X1=X2=X3

 ( 1)  X1_ - X2_ = 0
 ( 2)  X1_ - X3_ = 0

           chi2(  2) =   15.56
         Prob > chi2 =    0.0004

. estadd scalar equal=r(p)

added scalar:
              e(equal) =  .00041859

. test X1 X2 X3

 ( 1)  X1_ = 0
 ( 2)  X2_ = 0
 ( 3)  X3_ = 0

           chi2(  3) =   15.57
         Prob > chi2 =    0.0014

. estadd scalar all=r(p)

added scalar:
                e(all) =  .00138654

. 
. 
. ivreg2 R2 (X1 X2 X3 = Z1 Z2 Z3 ) yr70 yr80 yr90 $X tva* [w=pop50] if t>=70, c
> luster(state) partial($X yr70 yr80 yr90) ffirst
(analytic weights assumed)
(sum of wgt is     2.4294e+08)
Warning - collinearities detected
Vars dropped:       nowage20dum


Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  3,    42)  P-val | AP Chi-sq(  1) P-val | AP F(  1,    42)
X1_          |      89.74    0.0000 |      133.12   0.0000 |      129.06
X2_          |     102.85    0.0000 |      120.54   0.0000 |      116.87
X3_          |      49.86    0.0000 |       43.13   0.0000 |       41.82

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
                                    5% maximal IV relative bias    13.91
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(1)=21.75    P-val=0.0000

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                     195.17
Kleibergen-Paap Wald rk F statistic                                45.73

Stock-Yogo weak ID test critical values for K1=3 and L1=3:
                                                               <not available>
Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(3,42)=        4.10     P-val=0.0123
Anderson-Rubin Wald test           Chi-sq(3)=     12.68     P-val=0.0054
Stock-Wright LM S statistic        Chi-sq(3)=      8.54     P-val=0.0361

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =         43
Number of observations               N  =       5952
Number of regressors                 K  =          4
Number of endogenous regressors      K1 =          3
Number of instruments                L  =          4
Number of excluded instruments       L1 =          3
Number of partialled-out regressors/IVs =         41
NB: K & L do not included partialled-out variables

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     5952
                                                      F(  4,    42) =     3.86
                                                      Prob > F      =   0.0092
Total (centered) SS     =  665.2206278                Centered R2   =   0.0051
Total (uncentered) SS   =  665.2206278                Uncentered R2 =   0.0051
Residual SS             =  661.8513758                Root MSE      =    .3335

------------------------------------------------------------------------------
             |               Robust
          R2 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         X1_ |   .1090867    .044181     2.47   0.014     .0224935    .1956798
         X2_ |   .0485754   .0134479     3.61   0.000     .0222181    .0749328
         X3_ |   .0024054   .0024274     0.99   0.322    -.0023521     .007163
         tva |  -.0072622   .0187902    -0.39   0.699    -.0440903    .0295658
------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             21.750
                                                   Chi-sq(1) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):              195.167
                         (Kleibergen-Paap rk Wald F statistic):         45.727
Stock-Yogo weak ID test critical values:                       <not available>
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         X1_ X2_ X3_
Included instruments: tva
Excluded instruments: Z1_ Z2_ Z3_
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30 yr70 yr80 yr90
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum
------------------------------------------------------------------------------

. eststo spline4

. test X1=X2=X3

 ( 1)  X1_ - X2_ = 0
 ( 2)  X1_ - X3_ = 0

           chi2(  2) =   13.31
         Prob > chi2 =    0.0013

. estadd scalar equal=r(p)

added scalar:
              e(equal) =  .00128868

. test X1 X2 X3

 ( 1)  X1_ = 0
 ( 2)  X2_ = 0
 ( 3)  X3_ = 0

           chi2(  3) =   13.66
         Prob > chi2 =    0.0034

. estadd scalar all=r(p)

added scalar:
                e(all) =  .00340464

. 
. ivreg2 R2 (X1 X2 X3= Z1 Z2 Z3) yr70 yr80 yr90 $X tva* lnmanufdens40* [w=pop50
> ] if t>=70, cluster(state) partial($X yr70 yr80 yr90 lnmanufdens40*) ffirst
(analytic weights assumed)
(sum of wgt is     2.4294e+08)
Warning - collinearities detected
Vars dropped:       nowage20dum


Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  3,    42)  P-val | AP Chi-sq(  1) P-val | AP F(  1,    42)
X1_          |      84.58    0.0000 |      126.12   0.0000 |      122.25
X2_          |     106.30    0.0000 |      118.50   0.0000 |      114.87
X3_          |      45.80    0.0000 |       42.26   0.0000 |       40.96

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
                                    5% maximal IV relative bias    13.91
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(1)=21.45    P-val=0.0000

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                     192.68
Kleibergen-Paap Wald rk F statistic                                43.31

Stock-Yogo weak ID test critical values for K1=3 and L1=3:
                                                               <not available>
Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(3,42)=        4.57     P-val=0.0074
Anderson-Rubin Wald test           Chi-sq(3)=     14.13     P-val=0.0027
Stock-Wright LM S statistic        Chi-sq(3)=      9.00     P-val=0.0293

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =         43
Number of observations               N  =       5952
Number of regressors                 K  =          4
Number of endogenous regressors      K1 =          3
Number of instruments                L  =          4
Number of excluded instruments       L1 =          3
Number of partialled-out regressors/IVs =         42
NB: K & L do not included partialled-out variables

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     5952
                                                      F(  4,    42) =     4.29
                                                      Prob > F      =   0.0053
Total (centered) SS     =  661.0609749                Centered R2   =   0.0043
Total (uncentered) SS   =  661.0609749                Uncentered R2 =   0.0043
Residual SS             =  658.2010273                Root MSE      =    .3325

------------------------------------------------------------------------------
             |               Robust
          R2 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         X1_ |   .0961261    .044046     2.18   0.029     .0097974    .1824547
         X2_ |   .0494095   .0130667     3.78   0.000     .0237992    .0750198
         X3_ |    .002692   .0024761     1.09   0.277    -.0021611    .0075451
         tva |   -.000361   .0183467    -0.02   0.984    -.0363198    .0355978
------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             21.453
                                                   Chi-sq(1) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):              192.684
                         (Kleibergen-Paap rk Wald F statistic):         43.314
Stock-Yogo weak ID test critical values:                       <not available>
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         X1_ X2_ X3_
Included instruments: tva
Excluded instruments: Z1_ Z2_ Z3_
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30 yr70 yr80 yr90
                      lnmanufdens40
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum
------------------------------------------------------------------------------

. eststo spline5

. test X1=X2=X3

 ( 1)  X1_ - X2_ = 0
 ( 2)  X1_ - X3_ = 0

           chi2(  2) =   13.64
         Prob > chi2 =    0.0011

. estadd scalar equal=r(p)

added scalar:
              e(equal) =  .00109054

. test X1 X2 X3

 ( 1)  X1_ = 0
 ( 2)  X2_ = 0
 ( 3)  X3_ = 0

           chi2(  3) =   14.59
         Prob > chi2 =    0.0022

. estadd scalar all=r(p)

added scalar:
                e(all) =  .00219925

. 
. ivreg2 R2 (X1 X2 X3= Z1 Z2 Z3) yr70 yr80 yr90 $X tva* lnmanufdens40* regdum* 
> [w=pop50] if t>=70, cluster(state) partial($X yr70 yr80 yr90 lnmanufdens40* r
> egdum*) ffirst
(analytic weights assumed)
(sum of wgt is     2.4294e+08)
Warning - collinearities detected
Vars dropped:       nowage20dum regdum4


Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  3,    42)  P-val | AP Chi-sq(  1) P-val | AP F(  1,    42)
X1_          |      83.56    0.0000 |      124.96   0.0000 |      121.07
X2_          |     107.85    0.0000 |      120.40   0.0000 |      116.66
X3_          |      41.34    0.0000 |       33.06   0.0000 |       32.04

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
                                    5% maximal IV relative bias    13.91
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(1)=21.86    P-val=0.0000

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                     188.51
Kleibergen-Paap Wald rk F statistic                                45.82

Stock-Yogo weak ID test critical values for K1=3 and L1=3:
                                                               <not available>
Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(3,42)=        4.37     P-val=0.0091
Anderson-Rubin Wald test           Chi-sq(3)=     13.54     P-val=0.0036
Stock-Wright LM S statistic        Chi-sq(3)=      8.75     P-val=0.0329

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =         43
Number of observations               N  =       5952
Number of regressors                 K  =          4
Number of endogenous regressors      K1 =          3
Number of instruments                L  =          4
Number of excluded instruments       L1 =          3
Number of partialled-out regressors/IVs =         45
NB: K & L do not included partialled-out variables

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     5952
                                                      F(  4,    42) =     3.95
                                                      Prob > F      =   0.0083
Total (centered) SS     =  658.9923372                Centered R2   =   0.0059
Total (uncentered) SS   =  658.9923372                Uncentered R2 =   0.0059
Residual SS             =  655.1260357                Root MSE      =    .3318

------------------------------------------------------------------------------
             |               Robust
          R2 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         X1_ |   .0936022     .04376     2.14   0.032     .0078342    .1793701
         X2_ |   .0486051   .0129878     3.74   0.000     .0231495    .0740608
         X3_ |   .0022557   .0024113     0.94   0.350    -.0024703    .0069817
         tva |  -.0073822   .0178205    -0.41   0.679    -.0423097    .0275453
------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             21.856
                                                   Chi-sq(1) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):              188.507
                         (Kleibergen-Paap rk Wald F statistic):         45.822
Stock-Yogo weak ID test critical values:                       <not available>
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         X1_ X2_ X3_
Included instruments: tva
Excluded instruments: Z1_ Z2_ Z3_
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30 yr70 yr80 yr90
                      lnmanufdens40 regdum1 regdum2 regdum3
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum regdum4
------------------------------------------------------------------------------

. eststo spline6

. test X1=X2=X3

 ( 1)  X1_ - X2_ = 0
 ( 2)  X1_ - X3_ = 0

           chi2(  2) =   13.63
         Prob > chi2 =    0.0011

. estadd scalar equal=r(p)

added scalar:
              e(equal) =  .00109459

. test X1 X2 X3

 ( 1)  X1_ = 0
 ( 2)  X2_ = 0
 ( 3)  X3_ = 0

           chi2(  3) =   14.14
         Prob > chi2 =    0.0027

. estadd scalar all=r(p)

added scalar:
                e(all) =  .00272191

. 
. 
. esttab spline1 spline2 spline3 spline4 spline5 spline6 using $tables/g_tercil
> es_opt_sens.csv, replace cell( b(fmt(a2)) se(par fmt(a2)) first[APF](par([ ])
>  fmt(2) ) ) stat(equal all N, fmt(%6.0g))
(output written to ~/latex/tables_raw/g_terciles_opt_sens.csv)

. 
. 
. 
. **estimate wage coeff**
. ivreg2 D W X1 X2 X3 yr70 yr80 yr90 $X tva* [w=pop50] if t>=70, cluster(state)
>  partial($X yr70 yr80 yr90) ffirst
(analytic weights assumed)
(sum of wgt is     2.4474e+08)
Warning - collinearities detected
Vars dropped:       nowage20dum

Unable to display summary of first-stage estimates; macro e(first) is missing

OLS estimation
--------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     6057
                                                      F(  5,    42) =     4.34
                                                      Prob > F      =   0.0029
Total (centered) SS     =  233.5185055                Centered R2   =   0.0078
Total (uncentered) SS   =  233.5185055                Uncentered R2 =   0.0078
Residual SS             =  231.7063576                Root MSE      =    .1956

------------------------------------------------------------------------------
             |               Robust
           D |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
           W |  -.0455561   .0356137    -1.28   0.201    -.1153577    .0242455
         X1_ |   .0277001   .0083699     3.31   0.001     .0112953    .0441049
         X2_ |   .0097544   .0033014     2.95   0.003     .0032839    .0162249
         X3_ |  -.0001882   .0006718    -0.28   0.779    -.0015048    .0011285
         tva |   .0079078    .012623     0.63   0.531    -.0168329    .0326485
------------------------------------------------------------------------------
Included instruments: W X1_ X2_ X3_ tva
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30 yr70 yr80 yr90
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum
------------------------------------------------------------------------------

. eststo spline1

. test X1=X2=X3

 ( 1)  X1_ - X2_ = 0
 ( 2)  X1_ - X3_ = 0

           chi2(  2) =   17.26
         Prob > chi2 =    0.0002

. estadd scalar equal=r(p)

added scalar:
              e(equal) =  .00017864

. test X1 X2 X3

 ( 1)  X1_ = 0
 ( 2)  X2_ = 0
 ( 3)  X3_ = 0

           chi2(  3) =   17.30
         Prob > chi2 =    0.0006

. estadd scalar all=r(p)

added scalar:
                e(all) =  .0006137

. 
. ivreg2 D W X1 X2 X3 yr70 yr80 yr90 $X tva* lnmanufdens40* [w=pop50] if t>=70,
>  cluster(state) partial($X yr70 yr80 yr90 lnmanufdens40*) ffirst
(analytic weights assumed)
(sum of wgt is     2.4474e+08)
Warning - collinearities detected
Vars dropped:       nowage20dum

Unable to display summary of first-stage estimates; macro e(first) is missing

OLS estimation
--------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     6057
                                                      F(  5,    42) =     4.62
                                                      Prob > F      =   0.0019
Total (centered) SS     =  231.1882459                Centered R2   =   0.0076
Total (uncentered) SS   =  231.1882459                Uncentered R2 =   0.0076
Residual SS             =  229.4322829                Root MSE      =    .1946

------------------------------------------------------------------------------
             |               Robust
           D |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
           W |   -.048724   .0349602    -1.39   0.163    -.1172448    .0197968
         X1_ |   .0235215   .0084666     2.78   0.005     .0069274    .0401157
         X2_ |   .0107807   .0032819     3.28   0.001     .0043484    .0172131
         X3_ |  -.0001028   .0006834    -0.15   0.880    -.0014422    .0012366
         tva |   .0118089   .0122224     0.97   0.334    -.0121466    .0357644
------------------------------------------------------------------------------
Included instruments: W X1_ X2_ X3_ tva
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30 yr70 yr80 yr90
                      lnmanufdens40
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum
------------------------------------------------------------------------------

. eststo spline2

. test X1=X2=X3

 ( 1)  X1_ - X2_ = 0
 ( 2)  X1_ - X3_ = 0

           chi2(  2) =   16.08
         Prob > chi2 =    0.0003

. estadd scalar equal=r(p)

added scalar:
              e(equal) =  .00032217

. test X1 X2 X3

 ( 1)  X1_ = 0
 ( 2)  X2_ = 0
 ( 3)  X3_ = 0

           chi2(  3) =   16.21
         Prob > chi2 =    0.0010

. estadd scalar all=r(p)

added scalar:
                e(all) =  .0010274

. 
. ivreg2 D W X1 X2 X3 yr70 yr80 yr90 $X tva* lnmanufdens40* regdum* [w=pop50] i
> f t>=70, cluster(state) partial($X yr70 yr80 yr90 lnmanufdens40* regdum*) ffi
> rst
(analytic weights assumed)
(sum of wgt is     2.4474e+08)
Warning - collinearities detected
Vars dropped:       nowage20dum regdum4

Unable to display summary of first-stage estimates; macro e(first) is missing

OLS estimation
--------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     6057
                                                      F(  5,    42) =     4.50
                                                      Prob > F      =   0.0023
Total (centered) SS     =  230.6577952                Centered R2   =   0.0074
Total (uncentered) SS   =  230.6577952                Uncentered R2 =   0.0074
Residual SS             =  228.9486497                Root MSE      =    .1944

------------------------------------------------------------------------------
             |               Robust
           D |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
           W |  -.0501663   .0354309    -1.42   0.157    -.1196095    .0192769
         X1_ |   .0230391   .0084384     2.73   0.006     .0065001    .0395782
         X2_ |   .0105167   .0032569     3.23   0.001     .0041333    .0169001
         X3_ |  -.0001609   .0006448    -0.25   0.803    -.0014246    .0011029
         tva |   .0105961    .013274     0.80   0.425    -.0154204    .0366126
------------------------------------------------------------------------------
Included instruments: W X1_ X2_ X3_ tva
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30 yr70 yr80 yr90
                      lnmanufdens40 regdum1 regdum2 regdum3
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum regdum4
------------------------------------------------------------------------------

. eststo spline3

. test X1=X2=X3

 ( 1)  X1_ - X2_ = 0
 ( 2)  X1_ - X3_ = 0

           chi2(  2) =   15.70
         Prob > chi2 =    0.0004

. estadd scalar equal=r(p)

added scalar:
              e(equal) =  .00038929

. test X1 X2 X3

 ( 1)  X1_ = 0
 ( 2)  X2_ = 0
 ( 3)  X3_ = 0

           chi2(  3) =   15.80
         Prob > chi2 =    0.0012

. estadd scalar all=r(p)

added scalar:
                e(all) =  .00124887

. 
. 
. ivreg2 D W (X1 X2 X3 = Z1 Z2 Z3 ) yr70 yr80 yr90 $X tva* [w=pop50] if t>=70, 
> cluster(state) partial($X yr70 yr80 yr90) ffirst
(analytic weights assumed)
(sum of wgt is     2.4294e+08)
Warning - collinearities detected
Vars dropped:       nowage20dum


Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  3,    42)  P-val | AP Chi-sq(  1) P-val | AP F(  1,    42)
X1_          |      87.77    0.0000 |      133.32   0.0000 |      129.23
X2_          |     105.11    0.0000 |      119.55   0.0000 |      115.89
X3_          |      49.35    0.0000 |       43.81   0.0000 |       42.46

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
                                    5% maximal IV relative bias    13.91
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(1)=21.89    P-val=0.0000

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                     192.66
Kleibergen-Paap Wald rk F statistic                                45.78

Stock-Yogo weak ID test critical values for K1=3 and L1=3:
                                                               <not available>
Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(3,42)=        3.87     P-val=0.0156
Anderson-Rubin Wald test           Chi-sq(3)=     11.98     P-val=0.0074
Stock-Wright LM S statistic        Chi-sq(3)=      8.04     P-val=0.0452

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =         43
Number of observations               N  =       5952
Number of regressors                 K  =          5
Number of endogenous regressors      K1 =          3
Number of instruments                L  =          5
Number of excluded instruments       L1 =          3
Number of partialled-out regressors/IVs =         41
NB: K & L do not included partialled-out variables

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     5952
                                                      F(  5,    42) =     3.57
                                                      Prob > F      =   0.0088
Total (centered) SS     =  228.1844023                Centered R2   =  -0.0012
Total (uncentered) SS   =  228.1844023                Uncentered R2 =  -0.0012
Residual SS             =  228.4605109                Root MSE      =    .1959

------------------------------------------------------------------------------
             |               Robust
           D |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         X1_ |      .0604   .0227803     2.65   0.008     .0157515    .1050486
         X2_ |   .0222593   .0068928     3.23   0.001     .0087497    .0357688
         X3_ |   .0003741   .0010885     0.34   0.731    -.0017594    .0025076
           W |  -.0634511    .038027    -1.67   0.095    -.1379826    .0110803
         tva |   .0009172   .0129812     0.07   0.944    -.0245254    .0263598
------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             21.894
                                                   Chi-sq(1) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):              192.662
                         (Kleibergen-Paap rk Wald F statistic):         45.781
Stock-Yogo weak ID test critical values:                       <not available>
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         X1_ X2_ X3_
Included instruments: W tva
Excluded instruments: Z1_ Z2_ Z3_
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30 yr70 yr80 yr90
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum
------------------------------------------------------------------------------

. eststo spline4

. test X1=X2=X3

 ( 1)  X1_ - X2_ = 0
 ( 2)  X1_ - X3_ = 0

           chi2(  2) =   12.88
         Prob > chi2 =    0.0016

. estadd scalar equal=r(p)

added scalar:
              e(equal) =  .00159604

. test X1 X2 X3

 ( 1)  X1_ = 0
 ( 2)  X2_ = 0
 ( 3)  X3_ = 0

           chi2(  3) =   13.42
         Prob > chi2 =    0.0038

. estadd scalar all=r(p)

added scalar:
                e(all) =  .00380418

. 
. ivreg2 D W (X1 X2 X3= Z1 Z2 Z3) yr70 yr80 yr90 $X tva* lnmanufdens40* [w=pop5
> 0] if t>=70, cluster(state) partial($X yr70 yr80 yr90 lnmanufdens40*) ffirst
(analytic weights assumed)
(sum of wgt is     2.4294e+08)
Warning - collinearities detected
Vars dropped:       nowage20dum


Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  3,    42)  P-val | AP Chi-sq(  1) P-val | AP F(  1,    42)
X1_          |      82.78    0.0000 |      126.13   0.0000 |      122.25
X2_          |     108.69    0.0000 |      117.68   0.0000 |      114.05
X3_          |      45.45    0.0000 |       42.92   0.0000 |       41.60

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
                                    5% maximal IV relative bias    13.91
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(1)=21.60    P-val=0.0000

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                     190.44
Kleibergen-Paap Wald rk F statistic                                43.42

Stock-Yogo weak ID test critical values for K1=3 and L1=3:
                                                               <not available>
Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(3,42)=        3.82     P-val=0.0166
Anderson-Rubin Wald test           Chi-sq(3)=     11.81     P-val=0.0081
Stock-Wright LM S statistic        Chi-sq(3)=      7.86     P-val=0.0491

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =         43
Number of observations               N  =       5952
Number of regressors                 K  =          5
Number of endogenous regressors      K1 =          3
Number of instruments                L  =          5
Number of excluded instruments       L1 =          3
Number of partialled-out regressors/IVs =         42
NB: K & L do not included partialled-out variables

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     5952
                                                      F(  5,    42) =     3.96
                                                      Prob > F      =   0.0050
Total (centered) SS     =  225.8911895                Centered R2   =  -0.0000
Total (uncentered) SS   =  225.8911895                Uncentered R2 =  -0.0000
Residual SS             =  225.8958283                Root MSE      =    .1948

------------------------------------------------------------------------------
             |               Robust
           D |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         X1_ |   .0511165   .0232831     2.20   0.028     .0054825    .0967505
         X2_ |    .022877   .0068133     3.36   0.001     .0095233    .0362308
         X3_ |   .0005815   .0010886     0.53   0.593    -.0015522    .0027152
           W |  -.0647884   .0373653    -1.73   0.083     -.138023    .0084462
         tva |   .0058728    .012715     0.46   0.644    -.0190482    .0307938
------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             21.597
                                                   Chi-sq(1) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):              190.438
                         (Kleibergen-Paap rk Wald F statistic):         43.415
Stock-Yogo weak ID test critical values:                       <not available>
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         X1_ X2_ X3_
Included instruments: W tva
Excluded instruments: Z1_ Z2_ Z3_
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30 yr70 yr80 yr90
                      lnmanufdens40
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum
------------------------------------------------------------------------------

. eststo spline5

. test X1=X2=X3

 ( 1)  X1_ - X2_ = 0
 ( 2)  X1_ - X3_ = 0

           chi2(  2) =   12.24
         Prob > chi2 =    0.0022

. estadd scalar equal=r(p)

added scalar:
              e(equal) =  .00220048

. test X1 X2 X3

 ( 1)  X1_ = 0
 ( 2)  X2_ = 0
 ( 3)  X3_ = 0

           chi2(  3) =   12.30
         Prob > chi2 =    0.0064

. estadd scalar all=r(p)

added scalar:
                e(all) =  .00642087

. 
. ivreg2 D W (X1 X2 X3= Z1 Z2 Z3) yr70 yr80 yr90 $X tva* lnmanufdens40* regdum*
>  [w=pop50] if t>=70, cluster(state) partial($X yr70 yr80 yr90 lnmanufdens40* 
> regdum*) ffirst
(analytic weights assumed)
(sum of wgt is     2.4294e+08)
Warning - collinearities detected
Vars dropped:       nowage20dum regdum4


Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  3,    42)  P-val | AP Chi-sq(  1) P-val | AP F(  1,    42)
X1_          |      81.93    0.0000 |      125.00   0.0000 |      121.08
X2_          |     110.79    0.0000 |      119.56   0.0000 |      115.82
X3_          |      40.80    0.0000 |       33.57   0.0000 |       32.52

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
                                    5% maximal IV relative bias    13.91
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(1)=21.96    P-val=0.0000

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                     186.39
Kleibergen-Paap Wald rk F statistic                                45.81

Stock-Yogo weak ID test critical values for K1=3 and L1=3:
                                                               <not available>
Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(3,42)=        3.45     P-val=0.0250
Anderson-Rubin Wald test           Chi-sq(3)=     10.67     P-val=0.0137
Stock-Wright LM S statistic        Chi-sq(3)=      7.21     P-val=0.0654

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =         43
Number of observations               N  =       5952
Number of regressors                 K  =          5
Number of endogenous regressors      K1 =          3
Number of instruments                L  =          5
Number of excluded instruments       L1 =          3
Number of partialled-out regressors/IVs =         45
NB: K & L do not included partialled-out variables

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on state

Number of clusters (state) =        43                Number of obs =     5952
                                                      F(  5,    42) =     3.50
                                                      Prob > F      =   0.0098
Total (centered) SS     =  225.3438227                Centered R2   =   0.0007
Total (uncentered) SS   =  225.3438227                Uncentered R2 =   0.0007
Residual SS             =  225.1878096                Root MSE      =    .1945

------------------------------------------------------------------------------
             |               Robust
           D |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         X1_ |   .0500158   .0231452     2.16   0.031      .004652    .0953796
         X2_ |   .0217536     .00685     3.18   0.001     .0083277    .0351794
         X3_ |   .0004305   .0011043     0.39   0.697    -.0017339    .0025948
           W |  -.0658841   .0378739    -1.74   0.082    -.1401156    .0083474
         tva |   .0043616   .0136563     0.32   0.749    -.0224043    .0311275
------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             21.961
                                                   Chi-sq(1) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):              186.387
                         (Kleibergen-Paap rk Wald F statistic):         45.813
Stock-Yogo weak ID test critical values:                       <not available>
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         X1_ X2_ X3_
Included instruments: W tva
Excluded instruments: Z1_ Z2_ Z3_
Partialled-out:       lnelevmax lnelevrang lnarea lnpop20 lnpop20sq lnpop30
                      lnpop30sq popdifsq agrshr20 agrshr20sq agrshr30 agrshr30s
> q
                      manufshr20 manufshr30 nowage30dum lnwage20 lnwage30
                      notwage30dum lntwage30 lnemp20 lnemp30 urbshare20
                      urbshare30 lnfaval20 lnfaval30 lnmedhsval30 lnmedrnt30
                      white20 white20sq white30 white30sq pctil20 pctil30
                      PRADIO30 urate30 fbshr20 fbshr30 yr70 yr80 yr90
                      lnmanufdens40 regdum1 regdum2 regdum3
                      nb: small-sample adjustments account for
                          partialled-out variables
Dropped collinear:    nowage20dum regdum4
------------------------------------------------------------------------------

. eststo spline6

. test X1=X2=X3

 ( 1)  X1_ - X2_ = 0
 ( 2)  X1_ - X3_ = 0

           chi2(  2) =   11.06
         Prob > chi2 =    0.0040

. estadd scalar equal=r(p)

added scalar:
              e(equal) =  .00396292

. test X1 X2 X3

 ( 1)  X1_ = 0
 ( 2)  X2_ = 0
 ( 3)  X3_ = 0

           chi2(  3) =   11.15
         Prob > chi2 =    0.0109

. estadd scalar all=r(p)

added scalar:
                e(all) =  .01092509

. 
. 
. esttab spline1 spline2 spline3 spline4 spline5 spline6 using $tables/g_tercil
> es_opt_freewage.csv, replace cell( b(fmt(a2)) se(par fmt(a2)) first[APF](par(
> [ ]) fmt(2) ) ) stat(equal all N, fmt(%6.0g))
(output written to ~/latex/tables_raw/g_terciles_opt_freewage.csv)

. 
. 
. 
. 
. **info for graphs**
. qui ivreg2 R (LX1 LX2 LX3= LZ1 LZ2 LZ3) yr70 yr80 yr90 $X tva* [w=pop50] if t
> >=70, cluster(state) partial($X yr70 yr80 yr90) ffirst

. 
. di `thresh1' `thresh2'
1.66012282.7397955

. mat A=J(19,3,.)

. local j=1

. forvalues i=5(5)95{
  2.   local newcut `cutg`i''
  3.   di `newcut'
  4.   
.   if `newcut' <= `thresh1' {
  5.     lincom LX1*`newcut'
  6.   }
  7.   if `newcut' > `thresh1' {
  8.     lincom LX1*`thresh1' + LX2*(`newcut'-`thresh1')
  9.   }
 10.   if `newcut' > `thresh2' {
 11.     lincom LX1*`thresh1' + LX2*(`thresh2'-`thresh1') + LX3*(`newcut'-`thre
> sh2')
 12.   }
 13. 
.   mat A[`j',1]=`newcut'
 14.   mat A[`j',2]=r(estimate)
 15.   mat A[`j',3]=r(se)
 16.   local ++j
 17.   }
-2.3430384

 ( 1)  - 2.343038*LX1_ = 0

------------------------------------------------------------------------------
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -1.038087   .2381099    -4.36   0.000    -1.504774   -.5714005
------------------------------------------------------------------------------
-1.3160445

 ( 1)  - 1.316044*LX1_ = 0

------------------------------------------------------------------------------
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.5830758   .1337422    -4.36   0.000    -.8452058   -.3209459
------------------------------------------------------------------------------
-.55144622

 ( 1)  - .5514462*LX1_ = 0

------------------------------------------------------------------------------
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.2443192   .0560404    -4.36   0.000    -.3541564   -.1344821
------------------------------------------------------------------------------
-.03389599

 ( 1)  - .033896*LX1_ = 0

------------------------------------------------------------------------------
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0150177   .0034447    -4.36   0.000    -.0217691   -.0082663
------------------------------------------------------------------------------
.32553913

 ( 1)  .3255391*LX1_ = 0

------------------------------------------------------------------------------
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1442307   .0330827     4.36   0.000     .0793897    .2090716
------------------------------------------------------------------------------
.52203287

 ( 1)  .5220329*LX1_ = 0

------------------------------------------------------------------------------
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .2312876   .0530513     4.36   0.000      .127309    .3352662
------------------------------------------------------------------------------
.76606517

 ( 1)  .7660652*LX1_ = 0

------------------------------------------------------------------------------
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .3394065   .0778509     4.36   0.000     .1868215    .4919915
------------------------------------------------------------------------------
.96738201

 ( 1)  .967382*LX1_ = 0

------------------------------------------------------------------------------
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .4286003   .0983096     4.36   0.000      .235917    .6212836
------------------------------------------------------------------------------
1.168646

 ( 1)  1.168646*LX1_ = 0

------------------------------------------------------------------------------
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .5177707    .118763     4.36   0.000     .2849995    .7505418
------------------------------------------------------------------------------
1.328297

 ( 1)  1.328297*LX1_ = 0

------------------------------------------------------------------------------
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .5885043   .1349874     4.36   0.000     .3239339    .8530748
------------------------------------------------------------------------------
1.4917183

 ( 1)  1.491718*LX1_ = 0

------------------------------------------------------------------------------
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .6609084    .151595     4.36   0.000     .3637877    .9580292
------------------------------------------------------------------------------
1.6601228

 ( 1)  1.660123*LX1_ = 0

------------------------------------------------------------------------------
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .7355204    .168709     4.36   0.000     .4048568    1.066184
------------------------------------------------------------------------------
1.86397

 ( 1)  1.660123*LX1_ + .2038472*LX2_ = 0

------------------------------------------------------------------------------
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .8285286   .1860418     4.45   0.000     .4638933    1.193164
------------------------------------------------------------------------------
2.0264153

 ( 1)  1.660123*LX1_ + .3662924*LX2_ = 0

------------------------------------------------------------------------------
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .9026466   .2010519     4.49   0.000     .5085922    1.296701
------------------------------------------------------------------------------
2.2125767

 ( 1)  1.660123*LX1_ + .5524538*LX2_ = 0

------------------------------------------------------------------------------
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .9875855   .2192561     4.50   0.000     .5578513     1.41732
------------------------------------------------------------------------------
2.4605321

 ( 1)  1.660123*LX1_ + .8004092*LX2_ = 0

------------------------------------------------------------------------------
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   1.100719   .2447677     4.50   0.000     .6209829    1.580455
------------------------------------------------------------------------------
2.7397955

 ( 1)  1.660123*LX1_ + 1.079673*LX2_ = 0

------------------------------------------------------------------------------
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   1.228137    .274766     4.47   0.000     .6896052    1.766668
------------------------------------------------------------------------------
3.0569314

 ( 1)  1.660123*LX1_ + 1.396809*LX2_ = 0

------------------------------------------------------------------------------
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   1.372835   .3099818     4.43   0.000     .7652815    1.980388
------------------------------------------------------------------------------

 ( 1)  1.660123*LX1_ + 1.079673*LX2_ + .3171359*LX3_ = 0

------------------------------------------------------------------------------
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   1.375778   .3075642     4.47   0.000     .7729632    1.978593
------------------------------------------------------------------------------
3.5877025

 ( 1)  1.660123*LX1_ + 1.92758*LX2_ = 0

------------------------------------------------------------------------------
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   1.615007   .3707262     4.36   0.000     .8883967    2.341617
------------------------------------------------------------------------------

 ( 1)  1.660123*LX1_ + 1.079673*LX2_ + .847907*LX3_ = 0

------------------------------------------------------------------------------
           R |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   1.622876   .3697627     4.39   0.000     .8981543    2.347597
------------------------------------------------------------------------------

.   
.   svmat A

.   gen ub=A2+1.96*A3
(11423 missing values generated)

.   gen lb=A2-1.96*A3
(11423 missing values generated)

.   list A2 ub lb in 1/20

     +-----------------------------------+
     |        A2          ub          lb |
     |-----------------------------------|
  1. | -1.038087   -.5713919   -1.504783 |
  2. | -.5830758    -.320941   -.8452106 |
  3. | -.2443192     -.13448   -.3541584 |
  4. | -.0150177   -.0082661   -.0217692 |
  5. |  .1442307    .2090728    .0793886 |
     |-----------------------------------|
  6. |  .2312876    .3352681    .1273071 |
  7. |  .3394065    .4919943    .1868187 |
  8. |  .4286003    .6212872    .2359135 |
  9. |  .5177706     .750546    .2849953 |
 10. |  .5885043    .8530796     .323929 |
     |-----------------------------------|
 11. |  .6609085    .9580346    .3637823 |
 12. |  .7355204     1.06619    .4048507 |
 13. |  .8285286    1.193171    .4638866 |
 14. |  .9026466    1.296708     .508585 |
 15. |  .9875855    1.417328    .5578434 |
     |-----------------------------------|
 16. |  1.100719    1.580463    .6209741 |
 17. |  1.228137    1.766678    .6895953 |
 18. |  1.375778    1.978604    .7729521 |
 19. |  1.622876    2.347611     .898141 |
 20. |         .           .           . |
     +-----------------------------------+

. 
. ren A1 x_est

. ren A2 g_est

. ren ub ub_est

. ren lb lb_est

. drop A*

. 
. keep x_est g_est ub_est lb_est

. save gfuncgraph, replace
(note: file gfuncgraph.dta not found)
file gfuncgraph.dta saved

. 
. 
. 
. 
end of do-file
